fleslie {lefko3} | R Documentation |
Create Function-based Age-based (Leslie) Matrix Projection Model
Description
Function fleslie()
returns age-based (Leslie) MPMs corresponding to
the patches and occasions given, including the associated component
transition and fecundity matrices, data frames detailing the characteristics
of the exact ages corresponding to rows and columns in estimated matrices,
and a data frame characterizing the patch and occasion combinations
corresponding to these matrices.
Usage
fleslie(
year = "all",
patch = NULL,
prebreeding = TRUE,
data = NULL,
modelsuite = NULL,
surv_model = NULL,
fec_model = NULL,
paramnames = NULL,
supplement = NULL,
start_age = NA,
last_age = NA,
fecage_min = NA,
fecage_max = NA,
continue = TRUE,
inda = NULL,
indb = NULL,
indc = NULL,
surv_dev = 0,
fec_dev = 0,
density = NA,
fecmod = 1,
random.inda = FALSE,
random.indb = FALSE,
random.indc = FALSE,
negfec = FALSE,
reduce = FALSE,
simple = FALSE,
err_check = FALSE,
exp_tol = 700,
theta_tol = 1e+08,
sparse_output = FALSE
)
Arguments
year |
A variable corresponding to observation occasion, or a set
of such values, given in values associated with the year term used in linear
model development. Defaults to |
patch |
A variable designating which patches or subpopulations will have
matrices estimated. Defaults to |
prebreeding |
A logical value indicating whether the life history model
is a pre-breeding model. Defaults to |
data |
The historical vertical demographic data frame used to estimate
vital rates (class |
modelsuite |
One of two optional lists. THe first is an optional
|
surv_model |
A linear model predicting survival probability. This can be
a model of class |
fec_model |
A linear model predicting fecundity. This can be a model of
class |
paramnames |
A data frame with three columns, the first describing all
terms used in linear modeling, the second (must be called |
supplement |
An optional data frame of class |
start_age |
The age from which to start the matrix. Defaults to
|
last_age |
The final age to use in the matrix. Defaults to |
fecage_min |
The minimum age at which reproduction is possible. Defaults
to |
fecage_max |
The maximum age at which reproduction is possible. Defaults
to |
continue |
A logical value designating whether to allow continued
survival of individuals past the final age noted in the stageframe, using the
demographic characteristics of the final age. Defaults to |
inda |
Can be a single value to use for individual covariate |
indb |
Can be a single value to use for individual covariate |
indc |
Can be a single value to use for individual covariate |
surv_dev |
A numeric value to be added to the y-intercept in the linear
model for survival probability. Defaults to |
fec_dev |
A numeric value to be added to the y-intercept in the linear
model for fecundity. Defaults to |
density |
A numeric value indicating density value to use to propagate
matrices. Only needed if density is an explanatory term used in linear
models. Defaults to |
fecmod |
A scalar multiplier of fecundity. Defaults to |
random.inda |
A logical value denoting whether to treat individual
covariate |
random.indb |
A logical value denoting whether to treat individual
covariate |
random.indc |
A logical value denoting whether to treat individual
covariate |
negfec |
A logical value denoting whether fecundity values estimated to
be negative should be reset to |
reduce |
A logical value denoting whether to remove ages associated
solely with |
simple |
A logical value indicating whether to produce |
err_check |
A logical value indicating whether to append extra
information used in matrix calculation within the output list. Defaults to
|
exp_tol |
A numeric value used to indicate a maximum value to set
exponents to in the core kernel to prevent numerical overflow. Defaults to
|
theta_tol |
A numeric value used to indicate a maximum value to theta as
used in the negative binomial probability density kernel. Defaults to
|
sparse_output |
A logical value indicating whether to output matrices
in sparse format. Defaults to |
Value
If all inputs are properly formatted, then this function will return
an object of class lefkoMat
, which is a list that holds the matrix
projection model and all of its metadata. Its structure has the following
elements:
A |
A list of full projection matrices in order of sorted patches and
occasions. All matrices output in R's |
U |
A list of survival transition matrices sorted as in |
F |
A list of fecundity matrices sorted as in |
hstages |
Set to |
agestages |
Set to |
ahstages |
A data frame detailing the characteristics of associated ages, in the form of a modified stageframe including reproduction status. |
labels |
A data frame giving the patch and year of each matrix in order.
In |
dataqc |
A vector showing the numbers of individuals and rows in the vertical dataset used as input. |
matrixqc |
A short vector describing the number of non-zero elements in
|
modelqc |
This is the |
prob_out |
An optional element only added if |
Notes
Unlike rlefko2()
, rlefko3()
,
arlefko2()
, and rleslie()
, this function does not
currently distinguish populations.
This function will yield incorrect estimates if the models utilized incorporate state in occasion t-1, or any size or reproductive status terms.
Users may at times wish to estimate MPMs using a dataset incorporating
multiple patches or subpopulations, but without discriminating between those
patches or subpopulations. Should the aim of analysis be a general MPM that
does not distinguish these patches or subpopulations, the
modelsearch()
run should not include patch terms.
Input options including multiple variable names must be entered in the order of variables in occasion t+1 and t. Rearranging the order will lead to erroneous calculations, and may lead to fatal errors.
Care should be taken to match the random status of year and patch to the states of those variables within the modelsuite. If they do not match, then they will be treated as zeroes in vital rate estimation.
Individual covariates are treated as categorical only if they are set as
random terms. Fixed categorical individual covariates are currently not
allowed. However, such terms may be supplied if the modelsuite
option
is set to a vrm_input
object. In that case, the user should also set
the logical random switch for the individual covariate to be used to
TRUE
(e.g., random.inda = TRUE
).
See Also
flefko3()
flefko2()
aflefko2()
arlefko2()
rlefko3()
rlefko2()
rleslie()
Examples
data(lathyrus)
lathvert_base <- verticalize3(lathyrus, noyears = 4, firstyear = 1988,
patchidcol = "SUBPLOT", individcol = "GENET", blocksize = 9,
sizeacol = "Volume88", repstracol = "FCODE88", fecacol = "Intactseed88",
deadacol = "Dead1988", censorcol = "Missing1988", censorkeep = NA,
censor = TRUE, NAas0 = TRUE, NRasRep = TRUE, NOasObs = TRUE)
lathvert_base$feca3 <- round(lathvert_base$feca3)
lathvert_base$feca2 <- round(lathvert_base$feca2)
lathvert_base$feca1 <- round(lathvert_base$feca1)
lathvert_age <- subset(lathvert_base, firstseen > 1988)
lath_survival <- glm(alive3 ~ obsage + as.factor(year2), data = lathvert_age,
family = "binomial")
lath_fecundity <- glm(feca2 ~ obsage + as.factor(year2), data = lathvert_age,
family = "poisson")
mod_params <- create_pm(name_terms = TRUE)
mod_params$modelparams[22] <- "obsage"
lathmat2fleslie <- fleslie(year = "all", data = lathvert_age,
surv_model = lath_survival, fec_model = lath_fecundity,
paramnames = mod_params, fecage_min = 1)