Usage
makePostFecObjs(dataf,
fecConstants=data.frame(NA),fecNames=NA,
explanatoryVariables="size",
Family="gaussian",
Transform="none",
meanOffspringSize=NA,
sdOffspringSize=NA,
offspringSplitter=data.frame(continuous=1),
vitalRatesPerOffspringType=data.frame(NA),
fecByDiscrete=data.frame(NA),
offspringSizeExplanatoryVariables="1",
burnin=3000,nitt=50000)
Arguments
dataf
a dataframe with columns "size", "sizeNext", "stage",
"stageNext", "fec1", "fec2" or other names containing fec; up to
nine are currently possible (and note that ANY name containing
"fec" will be included and these MUST NOT be transforme
fecNames
a character vector containing the names of the columns of the dataframe from which fecundity data will be analysed (one column at a time). If the fecNames argument is not specified (as by default, NA), fecNames will be filled by the names of all column na
fecConstants
a dataframe containing the value by which
each of the fecundity transforms will be multplied in the
order defined by the alphabetical order of column names
containing "fec"; these might capture for example the probability
of e
explanatoryVariables
a character vector containing formulas describing the desired
explanatory variables (interactions, etc) in classical R
style, i.e. separated by `+', `*', `:'. Possible covariates include `size', 'size2' (size^2), `size3'
(size^3),`logsize' (lo
Family
a character vector containing the names of the
families to be used for the glms, e.g., binomial, poisson, etc. Again, these must appear in the
order defined by the alphabetical order of column names
containing "fec"
Transform
a character vector containing the names of the
transforms to be used for the response variables, e.g., log, sqrt,
etc. Again, these must appear in the
order defined by the alphabetical order of column names
containing "fec"
meanOffspringSize
numeric vector, defining mean offspring size. Defaults to NA, in which case the
function will use to data to assess the mean offspring size
sdOffspringSize
numeric vector, defining sd of offspring size. Defaults to NA, in which case the
function will use to data to assess the mean offspring size
offspringSplitter
dataframe, with column headings for EVERY
category, so always at minimum containing a column called "continuous" but also
including every discrete category that will enter into the Fmatrix (and, if
compatibility is required, the Pmatrix), with
vitalRatesPerOffspringType
dataframe defining which fecundity rates (both functions and constants) apply to which offspring category. This only needs to be
specified when some fecundity rates do not apply to all offspring categories. The offspring categories in the column name
fecByDiscrete
data.frame defining number of offspring produced by each
discrete class ; defaults to 0. If specified, ALL discrete classes MUST appear in alphabetical order, so NO "continuous". e.g. fecByDiscrete=data.frame(dormant=0,seedAge1=4.2,seedOld=0)
offspringSizeExplanatoryVariables
a character defining the relationship defining offspring size; the default is "1", indicating simply fitting a mean and a variance; alternatives would including defining offspring size as a function of maternal size (i.e., offspringSizeExplanatoryVariable
burnin
numeric defining burn in for MCMCglmm