occumbData {occumb}

Constructor for occumbData data class.

Description

occumbData() creates a data list compatible with the model fitting function occumb().

Usage

occumbData(y, spec_cov = NULL, site_cov = NULL, repl_cov = NULL)

Arguments

y

A 3-D array of sequence read counts (integer values) that may have a dimnames attribute. The dimensions are ordered by species, site, and replicate. The data for missing replicates are represented by zero vectors. NAs are not allowed.

spec_cov

A named list of species covariates. Each covariate can be a vector of continuous (numeric or integer) or discrete (logical, factor, or character) variables whose length is dim(y)[1] (i.e., the number of species). NAs are not allowed.

site_cov

A named list of site covariates. Each covariate can be a vector of continuous (numeric or integer) or discrete (logical, factor, or character) variables whose length is dim(y)[1] (i.e., the number of sites). NAs are not allowed.

repl_cov

A named list of replicate covariates. Each covariate can be a matrix of continuous (numeric or integer) or discrete (logical or character) variables with dimensions equal to dim(y)[2:3] (i.e., number of sites \times number of replicates). NAs are not allowed.

Details

The element (i.e., covariate) names for spec_cov, site_cov, and repl_cov must all be unique. If y has a dimnames attribute, it is retained in the resulting occumbData object, and can be referenced in subsequent analyses.

Value

An S4 object of the occumbData class.

Examples

# Generate the smallest random dataset (2 species * 2 sites * 2 reps)
I <- 2 # Number of species
J <- 2 # Number of sites
K <- 2 # Number of replicates
data <- occumbData(
    y = array(sample.int(I * J * K), dim = c(I, J, K)),
    spec_cov = list(cov1 = rnorm(I)),
    site_cov = list(cov2 = rnorm(J), cov3 = factor(1:J)),
    repl_cov = list(cov4 = matrix(rnorm(J * K), J, K))
)

# A case for named y (with species and site names)
y_named <- array(sample.int(I * J * K), dim = c(I, J, K))
dimnames(y_named) <- list(c("common species", "uncommon species"),
                          c("good site", "bad site"), NULL)
data_named <- occumbData(
    y = y_named,
    spec_cov = list(cov1 = rnorm(I)),
    site_cov = list(cov2 = rnorm(J), cov3 = factor(1:J)),
    repl_cov = list(cov4 = matrix(rnorm(J * K), J, K))
)

# A real data example
data(fish_raw)
fish <- occumbData(
    y = fish_raw$y,
    spec_cov = list(mismatch = fish_raw$mismatch),
    site_cov = list(riverbank = fish_raw$riverbank)
)

# Get an overview of the datasets
summary(data)
summary(data_named)
summary(fish)