stablestage3.list {lefko3}

Estimate Stable Stage Distribution of a List of Projection Matrices

Description

stablestage3.list() returns the stable stage distributions for stages in population projection matrices arranged in a general list. The function makes no assumptions about whether the matrix is ahistorical and simply provides stable stage distribution values corresponding to each row, meaning that the overall stable stage distribution of basic life history stages in a historical matrix are not provided (the stablestage3.lefkoMat() historical estimates these on the basis of stage description information provided in the lefkoMat object used as input in that function). This provided in the handle large and sparse matrices, and so can be used with large historical matrices, IPMs, age x stage matrices, as well as smaller ahistorical matrices.

Usage

## S3 method for class 'list'
stablestage3(
  mats,
  stochastic = FALSE,
  times = 10000,
  tweights = NA,
  seed = NA,
  force_sparse = "auto",
  ...
)

Arguments

mats

A list of population projection matrices, all in either class matrix or class dgCMatrix.

stochastic

A logical value indicating whether to use deterministic (FALSE) or stochastic (TRUE) analysis. Defaults to FALSE.

times

An integer variable indicating number of occasions to project if using stochastic analysis. Defaults to 10000.

tweights

An optional numeric vector or matrix denoting the probabilities of choosing each matrix in a stochastic projection. If a matrix is input, then a first-order Markovian environment is assumed, in which the probability of choosing a specific annual matrix depends on which annual matrix is currently chosen. If a vector is input, then the choice of annual matrix is assumed to be independent of the current matrix. Defaults to equal weighting among matrices.

seed

A number to use as a random number seed in stochastic projection.

force_sparse

A text string indicating whether to use sparse matrix encoding ("yes") when supplied with standard matrices. Defaults to "auto", in which case sparse matrix encoding is used with square matrices with at least 50 rows and no more than 50% of elements with values greater than zero.

...

Other parameters.

Value

This function returns a list of vector data frames characterizing the stable stage distributions for stages of each population projection matrix.

Notes

Speed can sometimes be increased by shifting from automatic sparse matrix determination to forced dense or sparse matrix projection. This will most likely occur when matrices have between 30 and 300 rows and columns. Defaults work best when matrices are very small and dense, or very large and sparse.

See Also

stablestage3()

stablestage3.lefkoMat()

stablestage3.matrix()

stablestage3.dgCMatrix()

Examples

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)

lathsupp3 <- supplemental(stage3 = c("Sd", "Sd", "Sdl", "Sdl", "Sd", "Sdl", "mat"),
  stage2 = c("Sd", "Sd", "Sd", "Sd", "rep", "rep", "Sdl"),
  stage1 = c("Sd", "rep", "Sd", "rep", "npr", "npr", "Sd"),
  eststage3 = c(NA, NA, NA, NA, NA, NA, "mat"),
  eststage2 = c(NA, NA, NA, NA, NA, NA, "Sdl"),
  eststage1 = c(NA, NA, NA, NA, NA, NA, "NotAlive"),
  givenrate = c(0.345, 0.345, 0.054, 0.054, NA, NA, NA),
  multiplier = c(NA, NA, NA, NA, 0.345, 0.054, NA),
  type = c(1, 1, 1, 1, 3, 3, 1), type_t12 = c(1, 2, 1, 2, 1, 1, 1),
  stageframe = lathframe, historical = TRUE)

ehrlen3 <- rlefko3(data = lathvert, stageframe = lathframe, year = "all", 
  stages = c("stage3", "stage2", "stage1"), supplement = lathsupp3,
  yearcol = "year2", indivcol = "individ")

ehrlen3mean <- lmean(ehrlen3)
stablestage3(ehrlen3mean$A)