lefko3 (version 3.1.0)

repvalue3.lefkoMat: Estimate Reproductive Value for a lefkoMat Object

Description

repvalue3.lefkoMat() returns the reproductive values for stages in a set set of population projection matrices provided as a lefkoMat object. This function can 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 lefkoMat
repvalue3(mats)

Arguments

mats

An object of class lefkoMat object.

Value

This function returns the reproductive values for stages of a matrices within a lefkoMat object. The nature of the output depends on whether the lefkoMat object used as input is ahistorical or historical. In both cases, raw reproductive values are estimated as the left eigenvector associated with the largest real part of the dominant eigenvalue, divided by the first non-zero element of the left eigenvector. Eigen analysis is handled by the eig_gen() function in the C++ Armadillo library for square matrices with fewer than 400 rows, and eigs_gen() for larger matrices.

If an ahistorical matrix set is used as input, then the output is a data frame that includes the number of the matrix within the $A element of the input lefkoMat object, followed by the numeric stage designation, the stage name, and the reproductive value estimated (repvalue).

If a historical matrix set is used as input, then a list with two elements is output. The first element is a data frame showing the reproductive values given given in terms of across-year stage pairs, as estimated in the procedure described above. The order of variables in the data frame is: the matrix of origin, the stage names for stages in times t and t-1 respectively, the numeric stage designations corresponding to these stages, and the reproductive value (rep_value). The second element is a data frame showing the reproductive values of the basic stages in the associated stageframe. The reproductive values in this second data frame are estimated via the approach developed in Ehrlen (2000), in which each ahistorical stage's reproductive value is the average of the RVs summed by stage at time t weighted by the proportion of that stage pair within the historical stable stage distribution associated with the matrix.

See Also

repvalue3()

repvalue3.matrix()

Examples

# 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)

lathrepm <- matrix(0, 7, 7)
lathrepm[1, 6] <- 0.345
lathrepm[2, 6] <- 0.054

lathover3 <- overwrite(stage3 = c("Sd", "Sd", "Sdl"), stage2 = c("Sd", "Sd", "Sd"), 
                       stage1 = c("Sd", "rep", "rep"), givenrate = c(0.345, 0.054))

ehrlen3 <- rlefko3(data = lathvert, stageframe = lathframe, year = c(1989, 1990), 
                   stages = c("stage3", "stage2", "stage1"), repmatrix = lathrepm, 
                   overwrite = lathover3, yearcol = "year2", 
                   indivcol = "individ", reduce = TRUE)

ehrlen3mean <- lmean(ehrlen3)
repvalue3(ehrlen3mean)

# }