Whatsnew: Summary of changes by version
Description
A good place to look for changes. Often I'll add changes
here but don't always get to it in the documentation for
awhile. They are ordered from newest to oldest.Details
Version 2.0.9 (1 Dec 2011) - Patch was made
to
make.mark.modelto fix bug in PIM
creation for a multi-session model and there was just 1
session. Thanks to Erin Roche for helping to identify
this bug. - Patch was made to
make.mark.modelto fix bug in handling of
mlogits for pi and Omega parameters with more than one
group. These parameters were introduced with the
RDMSMisClass and other new models that were recently
added. - Additional changes were made to
export.MARKto re-fix changes for robust
and nest survival model export to MARK. - A function
mark.wrapper.parallelwritten by Eldar
Rakhimberdiev provides a parallel processing version of
mark.wrapper. See the example in the help for the
function. The parallel version is functionally the same
and can be used in place ofmark.wrapperto run
sequentially or in parallel. It does not include the run
argument however. - A bug was fixed in
get.realwhich caused an R error for a
triangular PIM that had only a single entry. Thanks to
Amanda Goldberg for discovering and reporting this error.
Version 2.0.8 (7 Oct 2011) - Both
setup.modelandsetup.parameterswere re-written to use
data files models.txt and parameters.txt to define models
and parameters which should make it easier to add new
models. The latter function is now much simpler and
smaller. - Model RDOccupEG now allows sharing Epsilon
and Gamma parameters. Epsilon is the dominant parameter
which gets the share=TRUE argument. See
RDOccupancyfor an example. Thanks to Jake
Ivan for an example of what was needed. - To avoid
confusion, the arguments
componentandcomponent.namewere removed from the parameter
specification because these have not been required since
v1.3 when full support for individual covariates were
included. Likewise the argumentcovariatesinmarkandmake.mark.modelwas
removed because it was only needed to support the
component approach. export.MARKwas
modified so that if all individual covariates are output,
it excludes factor covariates.- Many more models
were added to those supported in RMark. Now 92 of the 137
models in MARK are supported. See MarkModels.pdf in the
RMark directory of your R library to see which models are
supported (in red). Most of the remaining unsupported
models are versions with mis-identification error and
they are not shown in MarkModels.pdf.
- Previously
RMark stored the input file in a temporary file
Markxxx.tmp. Using a common filename caused problems when
more than one model were spawned to different CPUs, so
now it uses a random temporary file name. It also no
longer uses common file markxxx.vcv. Thanks to Glenn
Stauffer for testing these changes.
- Sessions are
now labelled using value of session time rather than
numerically from 1 to largest session number in robust
designs. Thanks to Tommy Garrison for this suggestion.
- A bug was fixed in
get.realwhich
caused incorrect assignments of fixed parameter values in
the unusual case where a fixed parameter had a non-zero
design matrix row. mark.wrapperwas
modified so it returns a list of the models that were
constructed if run==FALSE. Thanks to Eldar Rakhimberdiev
for the suggestion and code.- Code was added to
extract.mark.outputto extract deviance
degrees of freedom. Thanks again to Eldar for
contributing this code. - A bug was fixed in
make.mark.modelthat prevented use of sin
link on within session parameters in a robust design
model. Thanks to Tommy Garrison for reporting this bug. - A bug was fixed in
make.mark.modelwhich prevented the use of time varying covariates with
shared parameters. Thanks to Andre Breton for reporting
this bug. - simplify argument was removed from
functions because I have not found a reason not to
simplify and I have not been testing code with
simplify=FALSE.
Version 2.0.7 (25 August 2011)
- Change to
make.mark.modelto fix bug in which mlogits were incorrectly assigned in
ORDMS model when both Psi and pent used mlogit links.
Thanks to Glenn Stauffer for identifying and tracking
down this error. - Fixed
export.chdataandexport.MARKso Nest survival models can
be exported. Also changed default of argument
ind.covariates to "all" which will use all individual
covariates in the data in the file sent to MARK. Thanks
to Jay Rotella for his help. - Made change to
process.dataandmarkto
include a new argument reverse, which if set to TRUE with
model="Multistratum" will reverse the timing of
transition and survival. Seemstratafor an
example of a reverse multistratum model. - Made
change to
make.design.datato allow for
zero time intervals in non-robust design model. This was
needed to allow use of the reverse time structure in
multi-state models. In addition, for the reverse
multistate model the function now adds an occasion (occ)
field to the design data because the time field will be
constant when with a 0 time interval. The row names of
the design matrix and real parameters was extended for
this model to include occasion (o) and occasion cohort
(oc) to create unique labels because cohort and time are
not unique with 0 time intervals.
Version 2.0.6 (1
July 2011) - Change to MR resight examples
so the output does not appear in notepad which was
causing problem with check on CRAN submission
Version
2.0.5 (29 June 2011) - Order of arguments
for
model.average.marklistwere switched
incorrectly such that ... was the second argument. This
has been fixed to the original format where ... is at the
end. This resulted in the value of any arguments other
than the first to be ignored unless specifically named
e.g.,parameter="Phi". Thanks to Rod Towell for
reporting this error. - Additional changes were made
to .First.lib to 1) examine any MarkPath setting, 2) look
in C:/program files/mark or c:/program files (x86)/mark,
3) or to search the path. If MARK executable cannot be
found in any of those ways then a warning is issued that
the user needs to set MarkPath to the path specification
for the location of the MARK executable. Thanks to Bryan
Wright for help with tracking down a bug.
- A bug in
add.design.datawas fixed where the
function gave incorrect results in pim.type was anything
other than "all". Thanks to Jeff Hostetler for reporting
this error. - The mark-resight models PoissonMR,
LogitNormalMR, and IELogitNormalMR were added. This
required some changes to
make.mark.model,make.design.dataandcompute.design.dataand the addition of
an argumentcountstoprocess.datato provide mark-resight count data that are not in the
capture history format. The format forcountsis a
named list of vectors (one group) or matrices (each group
is a row) where the names of the list elements are
specific to the model. Currently there is no checking to
make sure these are named correctly. Some of these models
are very sensitive to starting values; thus the use of
initial values in the examples. Thanks to Brett
McClintock for his help incorporating these models.
Version 2.0.4 (1 June 2011) - Change made
to .First.lib to check for availability of mark software
that depends on operating system. It now provides a
warning rather than stopping package attachment. This
allows the user to set MarkPath to some location outside
of default location Program Files or Program Files (x86)
without changing path which requires administrator
privilege on Windows.
- Change made to
run.mark.modelto use shQuote because link
to mark.exe was not working in some cases.
Version
2.0.3 (17 May 2011) - Now requires R 2.13
to use path.package function
- Change made to
.First.lib to check for availability of mark software
that depends on operating system.
Version 2.0.2 (16 May
2011) - MarkPath no longer needs to be set
if mark.exe is no longer in the default location
(c:/Program Files/mark) but is specified in the path. The
code now uses the R function Sys.which to find the
correct location for mark.exe, if it is contained in the
Path.
- Code for crm models was removed from RMark
and moved to a different R package called marked that is
under-development. This removes the FORTRAN code and
accompanying dll and some functions and help files that
were extraneous to RMark capabilities. There is still
some code in some functions for crm that could be removed
at some point. None of this matters to those who use
RMark for its original purpose as an interface to
mark.exe.
- Many superficial changes were made to
code so it could be posted on CRAN. Three changes that
may be noticed by users involved renaming
deriv.inverse.link, summary.ch and
merge.design.covariates to deriv_inverse.link,
summary_ch, and merge_design.covariates. These names
conflicted with the generic functions deriv, summary and
merge. It is only the last 2 that you may have in your
scripts and you will have to rename them. The deprecated
function merge.occasion.data was removed. Sorry for any
inconvenience.
- The dependency on Hmisc for the
examples was removed by replacing errbar with plotCI.
Version 2.0.1 (21 Feb 2011) - Made a change
to
run.mark.modelto handle output
filenames that exceeded mark9999. - Added an argument
prefixinmark,run.mark.modelandcleanup.
Like other parameters formark, it can also
be used inmark.wrapperas one of the ...
arguments. Previously the mark files have always been
named "marknnn.*". By specifyingprefixyou can
now create sets of models with different prefixes. For
example,prefix="cu"would result in
cu001.*(cu001.out, cu001.inp, etc), cu002.* etc. This
provides the ability to name files to do things like
naming them based on the species being analyzed. In
general, there is no need to work with these files
directly because the filename.* is stored with eachmarkobject and the various R functions use that
link to provide the information from the files. If you
use prefixes other than "mark", you'll need to call callcleanupwith each prefix to remove unused
files. Seerun.mark.modelfor an example
that shows use of the prefix argument to split the dipper
data into separate analyses for each sex. Note that use
of prefix was not mandatory here to separate the analyses
but it provided a useful example. - Additional
usefulness has been coded for argument
initialfor
assigning initial values to beta parameters. Previously,
the options were either a vector of the same length as
the new model to be run or a previously run model in amarkobject from which equivalent betas are
extracted based on their names in the design matrix. Now
if the vector contains names for the elements they will
be matched with the new model like with the model option
for initial. If any betas in the new model are not
matched, they are assigned 0 as their initial value, so
the length of theinitialvector no longer needs
to match the number of parameters in the new model as
long as the elements are named. The names can be
retrieved either from the column names of the design
matrix or fromrownames(x$results$beta)wherexis the name of themarkobject. - Using the feature above, I added a new argument
use.initialtomark.wrapper. Ifuse.initial=TRUE, prior to running a model it
looks for the first model that has already been run (if
any) for each parameter formula and constructs aninitialvector from that previous run. For
example, if you provided 5 models for p and 3 for Phi in
a CJS model, as soon as the first model for p is run, in
the subsequent 2 models with different Phi models, the
initial values for p are assigned based on the run with
the first Phi model. At the outset this seemed like a
good idea to speed up execution times, but from the one
set of examples I ran where several parameters were at
boundaries, the results were discouraging because the
models converged to a sub-optimal likelihood value than
the runs using the default initial values. I've left
this option in but set its default value to FALSE. - A possibly more useful argument and feature was added to
mark.wrapperin the argumentinitial. Previously, you could useinitial=modeland it would use the estimates from
that model to assign initial values for any model in the
set defined inmark.wrapper. Now I've
definedinitialas a specific argument and it can
be used as above but you can also use it to specify amarklistof previously run models. When you do
that, the code will lookup each new model to be run in
the set of models specified byinitialand if it
finds one with the matching name then it will use the
estimates for any matching parameters as initial values
in the same way asinitial=modeldoes. The model
name is based on concatenating the names of each of the
parameter specification objects. To make this useful,
you'll want to adapt to an approach that I've started to
use of naming the objects something like p.1,p.2 etc
rather than naming them something like p.dot, p.time as
done in many of the examples. I've found that using
numeric approach is much less typing and cumbersome
rather than trying to reflect the formula in the name. By
default, the formula is shown in the model selection
results table, so it was a bit redundant. Now where I
see this being the most benefit. Individual covariate
models tend to run rather slowly. So one approach is to
run the sequence of models (eg results stored in
initial_marklist), including the set of formulas with all
of the variables other than individual covariates. Then
run another set with the same numbering scheme, but
adding the individual covariates to the formula and usinginitial=initial_marklistThat will work if each
parameter specification has the same name (eg.,
p.1=list(formula=~time) and then
p.1=list(formula=~time+an_indiv_covariate)). All of the
initial values will be assigned for the previous run
except for any added parameters (eg. an_indiv_covariate)
which will start with a 0 initial value. - I added a
new function
search.output.filesto the set
of utility functions. This can be useful to search all of
the output files in amarklistfor a specific
string like "numerical convergence suspect" or just
"WARNING". The function returns the model numbers in themarklistthat contain that string in the output
file. - Further changes were needed to
popan.derivedto handle data that are
summarized (i.e. frequency of capture history >1). Thanks
to Carl Schwarz for reporting and finding the change
needed. - A bug was fixed in
create.dmwas
fixed so it would return a matrix instead of a vector
with the formula ~1
Version 2.0.0 (14 Jan 2011)
- The packages msm, Hmisc, nlme, plotrix
are now explicitly required to install RMark. These were
used in examples or for specialty functions, but to avoid
problems these must be installed as well.
- Added
example for "CRDMS" model that was created by Andrew
Paul. See
crdms. - Change was made for
gamma link in v1.9.3 was only made to Pradel model and
not Pradsen like it stated. Both now correctly use the
logit link as the default for gamma. Thanks to Gina
Barton for bringing this to my attention.
- Change
was made in
make.mark.modelthat prevented
use of groups with Nest survival models. Thanks to Jeff
Warren for bringing this to my attention. - Change
was made in
make.design.databecause
re-ordering of parameters caused issues with the CRDMS
model because thesubtract.stratumwere not being
set forPsi.
Version 1.9.9 (2 Nov 2010)
- This version was built with R 2.12 and
will not work with earlier versions of R. It contains
both 32 and 64 bit versions and R will automatically
ascertain which to use.
- Parameter ordering for some
models (RDHet, RDFullHet, RDHHet, RDHFHet, OccupHet,
RDOccupHetPE, RDOccupHetPG, RDOccupHetEG, MSOccupancy,
ORDMS, and CRDMS) had to be changed such that the models
could be imported into the MARK interface. This change
can influence any code you have written for those models
if you specified parameter indices because the ordering
of the parameters were changed. For example, see change
in example for
RDOccupancyto use
indices=c(1) from c(10). Thanks to Gary White for
helping me work this out. - Modified code in
extract.mark.outputto handle cases with
more than 9999 real parameters because MARK outputs ****
when it exceeds 9999.
Version 1.9.8 (15 Sept 2010)
- Added
model="CRDMS"with
parameters S, Psi, N, p, and c for closed robust design
multi-state models - Patched
popan.derivedwhich produced incorrect
abundance estimates with unequal time intervals. Thanks
to Andy Paul for finding this error and testing for me. - Patched
export.MARKwhich failed for
robust design models. Thanks to Dave Hewitt and Gary
White for discovering and isolating the problem.
Version 1.9.7 (14 April 2010) - Added
model="Brownie"with parameters S and f which is
the Brownie et al. parameterization of the recovery
model. "Recovery only" (in RMark)model="Recovery"which is also encounter type "dead" in MARK uses the
Seber parameterization with parameters S and r which is
also used in the models for live and dead encounter
models. - Added
model="MSLiveDead"with
parameters S, r, Psi and p. It is the multistate version
of the Burnham model in which F=1. - Added
compute.Snto utility functions for
computation of natural survival from total survival when
all harvest is reported. Patchednat.survwhich was incorrectly rejecting based on model type. - Added
var.components.remlto provide
an alternate variance components estimation using REML or
maximum likelihood. It allows a random component that is
not iid which is all thatvar.componentscan do. - Replaced all T/F values with TRUE/FALSE to
avoid conflicts with objects named TRUE or FALSE.
Version 1.9.6 (1 February 2010) - Writing
the
popan.derivedfunction has led me down
all sorts of paths. I had to make one small change to
this function to handle externally saved models.
However, various changes listed below were brought on by
using this function with a relatively large POPAN model. - Most importantly I discovered an error in
computations of real parameters with an mlogit link in
which some of the real parameters involved in the mlogit
link were fixed. This is NOT a problem if you simply used
the real parameter values extracted from MARK; however,
if you were using either
compute.real(model.average uses this function) orcovariate.predictionsto compute those real
parameters (with an mlogit link) then they may be
incorrect. This would have been apparent because their
value would have changed relative to the original values
extracted from the MARK output. Correcting this error
involved changes incompute.real,convert.link.to.realandcovariate.predictionsto correct the real
parameter estimates and their standard errors. I've not
found it in the MARK documentation but deduced that if
you use the mlogit link and fix real parameters it uses
those fixed real parameter values in the calculation. A
simple example will make it clear. Consider pent for 5
occasions where the first is computed by subtraction and
you then have 4 real parameters. Let's assume that the
3rd and fourth parameters were fixed to 0. Then the real
parameters are calculated as follows:
pent2=exp(beta2)/(1+
exp(beta2)+exp(beta3)+exp(0)+exp(0)),
pent3=exp(beta3)/(1+
exp(beta2)+exp(beta3)+exp(0)+exp(0)), pent4=0, pent5=0
and pent1=1-pent2-pent3-0-0 (in this case). Obviously you
would not want to fix any real parameters to be >1, <0 or="" to="" have="" the="" sum="" be="" <0="">1. This structure also had
implications on how the standard error was calculated. - In addition the coding was made more efficient in
covariate.predictionsfor the case wheredata(index=somevector)is used without any data
entries for covariate values in the design matrix. While
the task performed with that use of the function could be
done withcompute.real, it is useful to
have the capability incovariate.predictionsas well because it
will then model average over the listed set of
parameters. The previous approach to coding was
inefficient and led to very large matrices that were
unnecessary and could cause failure with insufficient
memory for large analyses. - Calculation of NGross
was added to
popan.derivedand logical
argumentsNandNGrosswere added to
control what was computed in the call. In addition,
argumentdropwas added which is passed tocovariate.predictionsto control whether
models are dropped when variance of betas are not all
positive. var.componentswas
modified to use qr matrix inversion. The returned value
for beta is now a dataframe that includes the std errors
which are extracted from the vcv matrix. Also, if the
design matrix only uses a portion of the vcv matrix, the
appropriate rows and columns are now extracted. Prior to
this change, the standard errors would have been
unreliable if the design matrix didn't use the entire set
of thetas and vcv matrix.
Version 1.9.5 (4 December
2009) - A bug in
covariate.predictionswas fixed that would
assign fixed values incorrectly if the parameter indices
were specified in anything but ascending order. The
error would have been obvious to anyone that may have
encountered it because estimated parameters would likely
have been assigned a fixed value. In most cases indices
would be passed in order if they were selected from the
design data unless indices were chosen from more than one
parameter type. I discovered it using thepopan.derivedfunction I added in v1.9.4
because it requests indices for multiple parameters in a
single function call.
Version 1.9.4 (6 November 2009)
- Note that this version was built with R
2.10 which no longer supports compiled help files
(chtml). If you were using compiled help files to get
help with RMark, you'll need to switch to regular html
files by using options(help_type="html") in R. You can
put this command in your RProfile.site file so it is set
up that way each time you start R. The functionality is
the same but it is not as pretty. You can find the index
(what used to be in a window on the left) as a link at
the bottom of each help page.
- Changed
export.MARKso it will not allow selection
of a project name that would over-write an existing .inp
file. - Added the function
popan.derivedwhich for POPAN models
computes derived abundance estimates by group and
occasion and sum of group abundances for each occasion.
For some reason RMark is unable to extract all of the
derived parameters from the MARK binary file for POPAN
models. This function provides the derived abundance
estimates and their var-cov matrix and adds the abundance
estimate sum across groups for each occasion which is not
provided by MARK. Note that by default confidence
intervals are based on a normal distribution to match the
output of MARK, but if you want log-normal intervals usenormal=FALSE. - The
model.average.listandmodel.average.marklistfunctions were
modified to use revised estimator for the unconditional
standard error (eq 6.12 of Burnham and Anderson (2002))
which is now the default in MARK. To use eq 4.9 (the
prior formula) set the argumentrevised=FALSE. - Fixed bug in
model.average.listwhich
in some cases failed when the list of var-cov matrices
were specified. - Code in
model.average.marklistwas changed to set
standard error to 0 if the variance is negative. The
same is done in the var-cov matrix for the variance and
any corresponding covariances. The results from RMark
will now match the model average results from MARK for
this case. It is not entirely clear that this is the
best approach when ill-fitted models are included. - Changed code in
cleanupto handle case in
which a model did not run. - Changed use of
grepandregexprinconvert.inpandextract.mark.outputto accomodate change in
R.2.10. The code should work in earlier versions of R
but if not update to R2.10. - Created a function
adjust.valueand kept special case ofadjust.chat. For any field other thanchatit will adjust the value inmodel$results. As an
example, to adjust the effective sample size (ESS) usemodel.list=adjust.value("n",value,model.list)where value is replaced with the ESS you want to use. As
part of the changemodel.tablewas changed
to recompute AICc.
Version 1.9.3 (24 September 2009)
- Default link function for Gamma in the
Pradel seniority model had been incorrectly set to log
and has now been changed to logit to restrict it to be a
probability.
- A bug was fixed in
compute.realandcovariate.predictionsin which confidence
intervals were being incorrectly scaled by c (chat
adjustment) instead of sqrt(c). The reported standard
errors were correctly using sqrt(c) and only the
confidence intervals for the real predictions were too
large. Simply re-running the prediction computations for
a model will provide the correct results. There is no
reason to re-run the models. Also this in no way affects
model selection. - A related bug was fixed in
compute.realandcovariate.predictionswhich created invalid
confidence intervals for real parameters if a probability
link other than logit was used and a single type of link
was used for all real parameters (e.g., sin).
Version
1.9.2 (10 August 2009) - Added the function
export.MARKwhich creates a .Rinp, .inp and
optionally renames one or more output files for import to
MARK. The July 2009 version of MARK now contains a
File/RMARK Import menu item which will automatically
create the MARK project using the information in these
files. This prevents problems that have been encountered
in creating MARK projects with RMark output because the
data/group structures are setup exactly in MARK as they
were in RMark. Seeexport.MARKfor an
example and instructions. - Fixed a problem in
make.design.datawhich prevented use ofremove.unusedwith unequal time intervals and more
than one group. - At least one person has encountered
a problem with a very large number of parameters in which
RMark created the input file with PIMs written in
exponential notation for the larger indices. MARK will
not accept that format and it will fail. The solution to
this is to set the R option scipen to a positive number.
Start with options(scipen=1) and increase if necessary.
Version 1.9.1 (2 June 2009) - Fixed a
problem
make.design.datawhich was not
usingbegin.timeto label the session values - Made a change in
export.chdatalike the
change inmake.mark.modelto accomodate
change with release of version R2.9.0. - Made a
change in
process.dataso thatstrata.labelscan be specified for Multistrata
designs like with ORDMS so an unobserved strata can be
included. - A warning was added to the help file for
export.chdataandexport.modelso it is clear that the MARK
database must be created correctly and with the .inp file
created byexport.chdatafrom the processed
data that was used to create the models that are being
exported. This is to ensure that the group structure is
setup such that the assumed model structure for groups
matches the model structure setup in the .inp file.
Version 1.9.0 (30 April 2009) - Fixed a bug
in
summary.markwhich occasionally produced
erroneous results withshowall=FALSE. - Made a
change in
make.mark.modelto accomodate
change with release of version R2.9.0. - RMark now
requires R version 2.8.1 or higher.
Version 1.8.9 (9
March 2009) - Changed
model.average.marklistandcovariate.predictionsto set NaN or Inf
results in v-c matrix to 0 to cope with poorly determined
models. Also, for each function the dropping of models
is now restricted to cases in which there are negative
variances for the betas being used in the averaged
parameter estimates. Unused betas are ignored. For
example, ifmodel.averageis called withparameter="Phi", then the model will only be
dropped if there is a negative variance for one of the
betas associated with "Phi". - In
var.componentsthe tolerance value
(tol) in the call tounirootwas reduced to
1e-15 which should provide better estimates of the
process variance when it is small. Previously a process
variance less than 1e-5 would be treated as 0. - Made
changes to
cleanup,coef.mark, andmake.mark.modelto accomodate externally
saved model objects (external=TRUE).
Version
1.8.8 (5 December 2008) - An error was
fixed in
make.time.factorwhich created
incorrect assignments when only some of the time
dependent variables contained a "." for occasions with no
data. - Patched
compute.design.datawhich was not creating the design data in the same order
as the PIM construction for the newly addedORDMSmodel. - Generalized section of code in
make.mark.modelto handlemlogitstructure forORDMSmodel. - Fixed a bug in
process.datain which the initial ages were
not correctly assigned in some situations with multiple
grouping variables. Note that it is always a good idea
to examine the design data after it is created to make
sure it is structured properly because it relates the
data and model structure via the grouping variables and
the pre-defined variables (ie age, time etc), While I've
done a lot of testing, I have certainly not tried every
possible example and there is always the potential for an
error to occur in a circumstance that I've not
encountered.
Version 1.8.7 (13 November 2008) - An argument
common.zerowas added to
functionmake.design.dataandcompute.design.data. It can be set to TRUE
to make theTimevariable have a common time
origin ofbegin.timewhich is useful for shared
parameters likepandcin closed capture
and similar models. - The function
read.mark.binarywas patched to work with
the newer versions of MARK.EXE since 1 Oct 2008. - The model type
ORDMSfor open robust design
multi-state models was added. An example data set will be
added at a later date after further testing has been
completed. - Some patches were made to fix some
aspects of profile intervals and to fix adjustment by
chat in
summary.markwhenshowall=F.
The notation for profile intervals is now included in the
fieldmodel$results$real$notewheremodelis the name of a mark model. Previously an incomplete
notation was kept inmodel$results$real$fixedbut
that field is now used exclusively to denote fixed
parameters. It is important to realize that profile
intervals computed by MARK are only found inmodel$results$real$noteand are not changed by achatadjustment unless the model is re-run. None
of the intervals computed byRMarkand displayed
bysummary.markare profile intervals.
Version 1.8.6 (28 October 2008) - A bug in
an error message for
initial.agesinprocess.datawas fixed. - A new
function
var.componentswas added to
provide variance components capability as in the MARK
interface except that shrinkage estimators are not
computed currently. - Fixed parameter values are now
being reported correctly by
covariate.predictions. Also over-dispersion
(c>1) was not being included in the variances for
parameters except those using the mlogit link. - Some utility functions were added including
pop.est,nat.surv, andextract.indices. - The function
model.averagehas been changed to a generic
function. Currently it supports 2 classes: 1) list, and
2) marklist. The latter was the originalmodel.averagewhich has been renamedmodel.average.marklistand the first
argument has been renamedxinstead ofmodel.listto match the standard generic function
approach. The previous syntaxmodel.average(...)will work as long as the usage does not name the first
agument as in the examplemodel.average(model.list=dipper.results,...). The
list formulation (model.average.list) was
created to enable a generic model averaging of estimates
instead of just real parameter estimates from amarkmodel. It could be used with any set of
estimates, model weights and estimates of precision. - A change is needed to
read.mark.binaryto accomodate the change
to mark.exe with the version dated 1 Oct 2008. Some data
types (notably Nest survival) may not work with the new
version of mark.exe. Working with Gary to make the
patch. If you need an older version of mark.exe contact
me.
Version 1.8.5 (8 October 2008) - A
bug in
process.datawas fixed that
prevented use of a dataframe contained in a list while
using thegroupsargument. - Profile intervals
on the real parameters can now be obtained from MARK
using the arguments
profile.intand optionallychatinmark. The argumentprofile.intcan be set toTRUEand a
profile interval will be constructed for all real
parameters, or a vector of parameter indices can be
specified to restrict the profiling to certain
parameters. The value specified bychatis passed
to MARK for over-dispersion. - References to cjs, js
etc have been removed from here because this code was
removed 5/11/11.
- Yet another fix to
summary.chwhich gave incorrect results for
the number recaptured at least once whenmarray=Fand the data contained non-unity values forfreq.
Version 1.8.4 (29 August 2008) - A
generic function
coef.markwas added to
extract the table of betas from the model with the
expressioncoef(model)wheremodelis amarkmodel that has been run and contains output.
The table includes standard errors and confidence
intervals. - An argument
briefwas added tosummary.mark. Ifbrief=TRUEthe real
parameters are not included in the summary. - References to cjs, js etc have been removed from here
because this code was removed 5/11/11.
- A bug in
summary.chwas fixed. It would produce
erroneous results when the data contained a non-constantfreqfield. Results with the default offreq=1were fine. - The function
adjust.chatand its help file were changed
such that it was clear that amodel.listargument
was needed.
Version 1.8.3 (25 July 2008) - For robust design models, an error trap was added
to
process.datato make sure that the
capture history length matches the specification for thetime.intervals. This error was already trapped
for non-robust models. - Fixed an error in
make.mark.modelthat prevented interaction
model of session/time-specific individual covariates in a
robust design model. - Fixed an error in
process.dataso that the fieldfreqis optional for nest survival data sets. print.markwas modified to add an argumentinputwhich if set toinput=TRUEwill have
the MARK input file be displayed rather than the output
file. Also,wait=FALSEwas set in the system
command which means the viewer window will be opened and
you can carry on with R. Before you had to close the
viewer window before proceeding with R.- An example
RDOccupancyprovided by Bret Collier was
added for the Robust Occupancy model which shows the use
of session and time-varying individual covariates in a
robust design model.
Version 1.8.2 (26 June 2008)
summary.chwas modified to
allow missing cohorts (no captures/recaptures) for an
occasion and to fix a bug in whichbygroup=FALSEdid not work when groups were defined.- To avoid
running out of memory, an argument
externalhas
been added tocollect.models,mark,rerun.mark, andrun.mark.model. As with all arguments ofmark,externalcan also be set inmark.wrapper. Likewise,externalcan also be set inrun.modelsand it is
passed torun.mark.model. The default isexternal=FALSEbut if it is set toTRUEthen the mark model object is saved in an external file
with an extension.rdaand the same base filename
as its matching MARK output files. The mark object in the
workspace is a character string which is the name of the
file with the saved image (e.g., "mark001.rda"). Ifexternal=TRUEwithmark.wrapperthen
the resulting marklist contains a list entry for each
mark model which is only the filename and then the last
entry is themodel.table. All of the functions
recognize the dual nature of the mark object (i.e.,
filename or mark object) in the workspace. So even if
the mark object only contains the filename, functions
likeprint.markorsummary.markwill work. However, if you
have usedexternal=TRUEand you want to look at
part of a mark object without using one of the functions,
then use the functionload.model. Whereas, before
you may have typedmymark$results, if you useexternal=TRUE, you would replace the above withload.model(mymark)$results. - Functions
storeandrestorewere
created tostoreexternally andrestoremodels from external storage into the R workspace. They
work on amarklistand are only needed tostoreexternally existing marklist models or ones
originally created withexternal=FALSEor torestoreif you change your mind and decide to keep
them in the R workspace. - Error in setup for robust
design occupancy models with more than 2 primary sessions
was fixed. The error resulted in mark.exe crashing.
- The concept of time-varying individual covariates
has been expanded to include robust design models which
have both primary (session) and secondary (time)
occasion-specific data. For a robust design, a
time-varying individual covariate can be either
session-dependent or session-time dependent. As an
example, if there are 3 primary sessions and each has 4
secondary occasions, then the individual covariates can
be named x1,x2,x3 to be primary session-dependent or
named x11,x12,x13,x14,x21,x22,x23,x24,x31,x32,x33,x34.
The value of x can be any name for the covariate. In the
formula only the base name is used (e.g.,
~x) and
RMark fills in the individual covariate names that it
finds that match either the session or session-time
individual covariates.
Version 1.8.1 (19 May 2008)
- Added function
summary.chto provide summaries of the capture history data
(resighting matrices and m-arrays). It will not work with
all types of models at present. It will work with CJS
and Jolly-type models. - Added argument
model.nametomodel.tableto be able
to use alternate names in the model table. It can use
either the model name with each mark object which uses a
formula notation (the current approach) or it can use the
name of the R object containing the mark model
(model.name=FALSE). Seemodel.tablefor an example. Also, the help file formodel.tablewas updated to reflect the code
changes implemented in version 1.7.3. - Code in
mark.wrapperwas modified to output the
number of columns and column names of the design matrix
for each model ifrun=FALSE. This allows a check
of each of the columns included in the model. By
reviewing these you can assess whether the model was
constucted as you intended. If there is any question you
can either usemodel.matrixormake.mark.modelto examine the design
matrix more thoroughly. - A bug in the new function
merge.design.covariateswas fixed in whichmergewas sorting the design data which does
obvious bad things. Addingsort=FALSEdoes not
appear to mean that the data frame is left in its
original order. To prevent this, the dataframe is forced
to remain in its original order by adding a sequence
field for re-sorting after the merge.
Version 1.8.0 (8
May 2008) - Fixed a bug in
model.averagethat caused it to fail and
issue an error when any of the models included a time
dependent covariate in the parameter being averaged. - Added
merge.design.covariateswhich
is meant to replacemerge.occasion.data. This new
function allows covariates to be assigned bytime,timeandgroup, or justgroup. It
also uses a simplified list of arguments and works with
individual design dataframes rather than the entire ddl.
It uses the R functionmergewhich can be
used on its own to merge design covariates into the
design data. You can usemergedirectly as
this function only checks for some common mistakes before
it callsmergeand it handles reassignemnt of row
names in the case were design data have been deleted. An
example, where you might want to usemergeinstead
of this function would be situations where the design
data are not just group, time or group-time specific.
For example, if groups were specified by two different
factor variables say initial age and region and the
design covariates were only region-specific. It would be
more efficient to usemergedirectly rather than
this function which would require an entry for each group
which would be each pairing of inital age and region. If
you usemergeand you deleted design data
prior to merging, save the row.names, merge and then
reassign the row.names. - An argument
runwas
added tomark.wrapper. If set to FALSE,
then it will run through each set of models inmodel.listand try to build each model but does
not attempt to run it. This is useful to check for and
fix any errors in the formula before setting off a large
run. If you userun=FALSEdo not include arguments
that are meant to be passed torun.mark.modellikeadjust.
Version 1.7.9 (7 April 2008) make.design.datawas fixed so thatremove.unused=Twill work properly when differentbegin.timevalues are specified for each group.
Version 1.7.8 (12 March 2008) - Changed the
default link for N to log in the
setup.parametersfor theHetClosedandFullHet. It was incorrectly set to logit which
created incorrect estimates to be computed inmodel.averagebecause MARK forces the log
link for N regardless of what is set in the input file.
Version 1.7.7 (6 March 2008) - Supressed
warning message that occurred with code to check the
validity of the sin link in
make.mark.model. - Fixed a couple of
bugs in
covariate.predictionsthat
prevented it from working for some cases after including
code for the sin link. - Added function
release.gofto construct the RELEASE
goodness of fit test and extract the TEST2 and TEST3
final chi-square, df and P-values.
Version 1.7.6 (26
Feb 2008) make.mark.modelwas modified to change the capitalization of the link
functions and to remove all spaces after "=" in the input
file for mark.exe. These differences were preventing the
MARK interface from fully importing the model. Although
the model would be imported and could be run inside the
MARK interface, median c-hat would not run and would give
an error stating "Invalid Link" for any model imported
from RMark. Now transfering a model from RMark to the
MARK interface is fully functional (I hope). If you want
to import an output file that was created with a prior
version of RMark without re-running it, use a text editor
on the output file and remove any spaces before and after
an = sign. Then change the capitalization of the links
to "Logit", "MLogit", "Log", "LogLog", "CLogLog",
"Identity".- The sin link is now supported if the
formula for the parameter generates an identity matrix
for the parameter. For example, if you use ~-1+time
instead of ~time then the resulting design matrix will be
an identity for time. Likewise, for interactions use
~-1+group:time instead of ~group*time. If you select the
sin link and the resulting design matrix is not an
identity for the parameter, an error will be given and
the run will stop.
- To match the output from MARK,
the confidence intervals for real parameters using any
0-1 link including loglog,cloglog,logit and sin are now
computed using the logit transformation. For previous
versions this will only affect any results that were
using loglog and cloglog. Previously, it was using the
chosen link to compute the se and the interval endpoints.
The latter is still used for the log and identity links
which are not bounded in 0-1.
- The model "Jolly" was
added to the supported list of models. Parameters include
Phi,p,Lambda,N. It is not a particularly numerically
stable model and often will not converge. Use of
options="SIMANNEAL" in call to
markis
recommended for better convergence. It will take much
longer to converge but is mroe reliable.
Version 1.7.5
(24 Jan 2008) model.averagewas modified to ignore any models that did not run and
either had no attached output file or no results.read.mark.binaryandextract.mark.outputwere modified to
extract and store the real.vcv matrix (var-cov matrix of
the simplified real parameters) in the mark object if
realvcv=TRUE. The default is realvcv=FALSE. This argument
has been added to functionsmark,run.mark.modelandrerun.mark.- An argument delete has
also been added to
markandrun.mark.model. The default value is FALSE
but if set to TRUE it deletes all output files created by
MARK after extracting the results. This is most useful
for simulations that could easily create thousands of
output files and after extracting the results the model
objects are no longer needed. This is just a convenience
to replace the need to callcleanup.
Version 1.7.4 (10 Jan 2008) - A bug in
make.mark.modelwas fixed. It was
preventing creation of individual (site) covariate models
for parameters with only a single parameter (single
index) in certain circumstances like Psi1 in the
MSOccupancy model. - The fix to
merge.occasion.datain version 1.7.1 did not work
when design data had been deleted. That has been
remedied. - Various functions with some operating
specific calls have been modified so they will work on
either Windows or Linux. Thus, the there is a single
file for all source/help for both operating systems in
RMarkSource.zip. It can be downloaded to either Windows
or Linux to build the package. You need to build the
package for Linux but not for Windows. For Windows, you
only need RMark.zip which contains the pre-built package
which only needs to be installed. Currently, with Linux
the variable MarkPath is ignored and mark.exe is assumed
to be in the path. Also, for Linux the default for
MarkViewer is "pico" (an editor on some Linux machines).
This can be modified in
print.markor by
setting MarkViewer to a different value. The one Linux
specific function isread.mark.binary.linux. The
functionextract.mark.outputcalls eitherread.mark.binary.linuxorread.mark.binarydepending on the operating
system. A Linux version of mark.exe (32 or 64 bit) can be
obtained from Evan.
Version 1.7.3 (4 Jan 2008)
- In working with the occupancy models, it
became apparent that it would be useful to have a new
function called
make.time.factorwhich
creates time-varying dummy variables from a time-varying
factor variable. An example is given using observer with
the occupancy datasetwetafrom the
MacKenzie et al Occupancy modelling book. - To match
the results in the book, I added arguments
use.AICanduse.lnlto functionmodel.tableto construct a results table with AIC rather than AICc
and -2LnL values. The latter is more useful with a mix of
models some using individual covariates and others not. - A modification was made to
make.mark.modelwith theMSOccupancymodel to fix the name of the added data for parameterp1whenshare=TRUEto bep2. For an
example which uses p2 to construct an additive model, seeNicholsMSOccupancy.
Version 1.7.2 (20 Dec
2007) - In changing code for the occupancy
models, a brace was misplaced which prevented the nest
survival models from working. This has been fixed. Also,
the example code for
mallardandkilldeerwas modified to exclude the calls
to process the input file. This enables use of the
functionexample()to run the example code (e.g.example(mallard)). From now on as I add examples
they are being included in my test set to avoid this type
of problem in the future.
Version 1.7.1 (14 Dec 2007)
- If you update with this version of RMark
make sure to update MARK also, so you get the fixes for
some of the occupancy models.
- A minor bug was fixed
in function
merge.occasion.datathat created
duplicate row names and prevented the design data from
being used in a model. - Thirteen different occupancy
models were added. Models in the following list use the
designation from MARK:
Occupancy, OccupHet,
RDOccupEG, RDOccupPE, RDOccupPG, RDOccupHetEG,
RDOccupHetPE, RDOccupHetPG,OccupRNPoisson,OccupRNNegBin,OccupRPoisson,OccupRNegBin,MSOccupancy.Hetmeans it uses the Pledger mixture and those
withRDare the robust design models. The 2 letter
designations for the RD models are shorthand for the
parameters that are estimated. ForEG, Psi,
Epsilon, and Gamma are estimated, forPEgamma is
dropped and forPG, Epsilon is dropped. For the
latter 2 models, Psi can be estimated for each primary
occasion. The last 5 models include the Royle/Nichols
count (RPoisson) and presence (RNPoisson) models and the
multi-state occupancy model. Seesalamanderfor an example ofOccupancy, OccupHet,Donovan.7for
an example ofOccupRNPoisson,OccupRNNegBin,Donovan.8for an example ofOccupRPoisson,OccupRNegBin, seeRDSalamanderfor an example of the robust
design models andNicholsMSOccupancyfor an
example ofMSOccupancy.salamanderdata. - The functions
create.model.listandmark.wrapperwere modified so that a
list of parameters can be used to loop. This is useful
in the situation with shared parameters such asp1andp2in theMSOccupancymodel,closedmodels etc. Seep1.p2.different.dotinNicholsMSOccupancyfor an example. It
can also be useful if the model definitions are linked
conceptually (e.g., when one parameter is time dependent,
the other should also be time dependent). - The "."
value in an encounter history is now acceptable to RMark
and gets passed to MARK for interpretation as a missing
value.
print.marklistwas fixed to
show the model table properly after a c-hat adjustment
was made. The change in the code in version 1.6.5 to add
parameter specific values to the model table had the
side-effect of dropping the model name if c-hat was
adjusted.
Version 1.7.0 (7 Nov 2007)