verticalize3() returns a vertically formatted demographic data frame
organized to create historical projection matrices, given a horizontally
formatted input data frame.
verticalize3(
data,
noyears,
firstyear,
popidcol = 0,
patchidcol = 0,
individcol = 0,
blocksize,
xcol = 0,
ycol = 0,
juvcol = 0,
sizeacol,
sizebcol = 0,
sizeccol = 0,
repstracol = 0,
repstrbcol = 0,
fecacol = 0,
fecbcol = 0,
indcovacol = 0,
indcovbcol = 0,
indcovccol = 0,
aliveacol = 0,
deadacol = 0,
obsacol = 0,
nonobsacol = 0,
censorcol = 0,
repstrrel = 1,
fecrel = 1,
stagecol = 0,
stageassign = NA,
stagesize = NA,
censorkeep = 0,
censor = FALSE,
spacing = NA,
NAas0 = FALSE,
NRasRep = FALSE,
reduce = TRUE
)The horizontal data file.
The number of years or observation periods in the dataset.
The first year or time of observation.
A variable name or column number corresponding to the identity of the population for each individual.
A variable name or column number corresponding to the identity of the patch for each individual, if patches have been designated within populations.
A variable name or column number corresponding to the identity of each individual.
The number of variables corresponding to each time in the
input dataset designated in data.
A variable name or column number corresponding to the x coordinate of each individual in Cartesian space.
A variable name or column number corresponding to the y coordinate of each individual in Cartesian space.
A variable name or column number that marks individuals in
immature stages within the dataset. The verticalize3() function assumes
that immature individuals are identified in this variable marked with a number
equal to or greater than 1, and that mature individuals are marked as 0 or NA.
A variable name or column number corresponding to the size entry associated with the first year or observation time in the dataset.
A second variable name or column number corresponding to the size entry associated with the first year or observation time in the dataset.
A third variable name or column number corresponding to the size entry associated with the first year or observation time in the dataset.
A variable name or column number corresponding to the production of reproductive structures, such as flowers, associated with the first year or observation period in the input dataset. This can be binomial or count data, and is used to in analysis of the probability of reproduction.
A second variable name or column number corresponding to the production of reproductive structures, such as flowers, associated with the first year or observation period in the input dataset. This can be binomial or count data, and is used to in analysis of the probability of reproduction.
A variable name or column number denoting fecundity associated with the first year or observation time in the input dataset. This may represent egg counts, fruit counts, seed production, etc.
A second variable name or column number denoting fecundity associated with the first year or observation time in the input dataset. This may represent egg counts, fruit counts, seed production, etc.
A variable name or column number corresponding to an individual covariate to be used in analysis.
A variable name or column number corresponding to an individual covariate to be used in analysis.
A second variable name or column number corresponding to an individual covariate to be used in analysis.
A variable name or column number that provides information on whether an individual is alive at a given time. If used, living status must be designated as binomial (living = 1, dead = 0).
A variable name or column number that provides information on whether an individual is alive at a given time. If used, dead status must be designated as binomial (dead = 1, living = 0).
A variable name or column number providing information on whether an individual is in an observable stage at a given time. If used, observation status must be designated as binomial (observed = 1, not observed = 0).
A variable name or column number providing information on whether an individual is in an unobservable stage at a given time. If used, observation status must be designated as binomial (not observed = 1, observed = 0).
A variable name or column number corresponding to the first entry of a censor variable, used to distinguish between entries to use and entries not to use, or to designate entries with special issues that require further attention. If used, this should be associated with the first year or observation time, and all other years or times must also have censor columns.
This is a scalar multiplier on variable repstrbcol to
make it equivalent to repstracol. This can be useful if two reproductive
status variables have related but unequal units, for example if repstracol
refers to one-flowered stems while repstrbcol refers to two-flowered
stems. Defaults to 1.
This is a scalar multiplier on variable fecbcol to make it
equivalent to fecacol. This can be useful if two fecundity variables have
related but unequal units. Defaults to 1.
Optional variable name or column number corresponding to life history stage at a given time.
The stageframe object identifying the life history model
being operationalized. Note that if stagecol is provided, then this
stageframe is not used for stage designation.
A variable name or column number describing which size variable
to use in stage estimation. Defaults to NA, and can also take sizea, sizeb,
sizec, or sizeadded, depending on which size variable is chosen.
The value of the censor variable identifying data to be included in analysis. Defaults to 0, but may take any value including NA.
A logical variable determining whether the output data should be
censored using the variable defined in censorcol. Defaults to FALSE.
The spacing at which density should be estimated, if density
estimation is desired and x and y coordinates are supplied. Given in the same
units as those used in the x and y coordinates given in xcol and ycol.
Defaults to NA.
If TRUE, then all NA entries for size and fecundity variables will
be set to 0. This can help increase the sample size analyzed by modelsearch(),
but should only be used when it is clear that this substitution is biologically
realistic. Defaults to FALSE.
If TRUE, then will treat non-reproductive but mature individuals
as reproductive during stage assignment. This can be useful when a matrix is
desired without separation of reproductive and non-reproductive but mature
stages of the same size. Only used if stageassign is set to a stageframe.
Defaults to FALSE.
A logical variable determining whether unused variables and some invariant state variables should be removed from the output dataset. Defaults to TRUE.
If all inputs are properly formatted, then this function will output a
historical vertical data frame (class hfvdata), meaning that the output
data frame will have three consecutive times of size and reproductive data per
individual per row. This data frame is in standard format for all functions used
in lefko3, and so can be used without further modification.
Variables in this data frame include the following:
Unique identifier for the row of the data frame.
Unique identifier for the population, if given.
Unique identifier for patch within population, if given.
Unique identifier for the individual.
Year or time at time t.
Year or time of first observation.
Year or time of last observation.
Observed age in time t, assuming first observation corresponds to age = 0.
Observed lifespan, given as lastseen - firstseen + 1.
X position in Cartesian space in times t-1, t, and t+1, respectively, if provided.
Y position in Cartesian space in times t-1, t, and t+1, respectively, if provided.
Main size measurement in times t-1, t, and t+1, respectively.
Secondary size measurement in times t-1, t, and t+1, respectively.
Tertiary measurement in times t-1, t, and t+1, respectively.
Sum of primary, secondary, and tertiary size measurements in timea t-1, t, and t+1, respectively.
Main numbers of reproductive structures in times t-1, t, and t+1, respectively.
Secondary numbers of reproductive structures in times t-1, t, and t+1, respectively.
Sum of primary and secondary reproductive structures in times t-1, t, and t+1, respectively.
Main numbers of offspring in times t-1, t, and t+1, respectively.
Secondary numbers of offspring in times t-1, t, and t+1, respectively.
Sum of primary and secondary fecundity in times t-1, t, and t+1, respectively.
Censor state values in times t-1, t, and t+1, respectively.
Binomial variable indicating whether
individual is juvenile in times t-1, t, and t+1. Only given if
juvcol is provided.
Binomial observation state in times t-1, t, and t+1, respectively.
Binomial reproductive state in times t-1, t, and t+1, respectively.
Binomial offspring production state in times t-1, t, and t+1, respectively.
Binomial maturity state in times t-1, t, and t+1, respectively.
Binomial state as alive in times t-1, t, and t+1, respectively.
Density of individuals per unit designated in spacing. Only
given if spacing is not NA.
# NOT RUN {
data(lathyrus)
sizevector <- c(0, 100, 13, 127, 3730, 3800, 0)
stagevector <- c("Sd", "Sdl", "VSm", "Sm", "VLa", "Flo", "Dorm")
repvector <- c(0, 0, 0, 0, 0, 1, 0)
obsvector <- c(0, 1, 1, 1, 1, 1, 0)
matvector <- c(0, 0, 1, 1, 1, 1, 1)
immvector <- c(1, 1, 0, 0, 0, 0, 0)
propvector <- c(1, 0, 0, 0, 0, 0, 0)
indataset <- c(0, 1, 1, 1, 1, 1, 1)
binvec <- c(0, 100, 11, 103, 3500, 3800, 0.5)
lathframe <- sf_create(sizes = sizevector, stagenames = stagevector, repstatus = repvector,
obsstatus = obsvector, matstatus = matvector, immstatus = immvector,
indataset = indataset, binhalfwidth = binvec, propstatus = propvector)
lathvert <- verticalize3(lathyrus, noyears = 4, firstyear = 1988, patchidcol = "SUBPLOT",
individcol = "GENET", blocksize = 9, juvcol = "Seedling1988",
sizeacol = "Volume88", repstracol = "FCODE88",
fecacol = "Intactseed88", deadacol = "Dead1988",
nonobsacol = "Dormant1988", stageassign = lathframe,
stagesize = "sizea", censorcol = "Missing1988",
censorkeep = NA, censor = TRUE)
summary(lathvert)
# }
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