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Multinomial State-Space Model (mnTS)

mnTS.Rd

Fits a multinomial state-space model for multivariate count data, allowing for latent temporal processes, covariate effects, and species interactions.

Usage

mnTS(
  Y,
  X = NULL,
  Tsample = 1:nrow(Y),
  B0.fixed = matrix(c(0, rep(NA, ncol(Y) - 1)), nrow = 1, ncol = ncol(Y)),
  B0.start = matrix(0, nrow = 1, ncol = ncol(Y)),
  C.fixed = diag(rep(NA, ncol(Y))),
  C.start = 0.01 * diag(ncol(Y)),
  B.fixed = if (is.null(X)) NULL else matrix(NA, nrow = ncol(X), ncol = ncol(Y)),
  B.start = if (is.null(X)) NULL else matrix(0, nrow = ncol(X), ncol = ncol(Y)),
  sigma.fixed = NA,
  sigma.start = 0.1,
  dispersion.fixed = 1,
  dispersion.start = 1,
  V.fixed = diag(ncol(Y)),
  V.start = diag(ncol(Y)),
  compute.information.matrix = TRUE,
  method = "bobyqa",
  optim.control = NULL,
  maxit.optim = 1e+05,
  hessian.method.args = list(eps = 1e-04, d = 1e-04, r = 4, v = 2)
)

Arguments

Y

A matrix of multinomially distributed count data (e.g., community count data).

X

A matrix of covariates (predictors), which may be of mixed type. Covariates should be scaled when appropriate. Can be NULL.

Tsample

A vector of row indices specifying the subset of observations in Y to treat as temporal samples.

B0.fixed

A 1 by ncol(Y) matrix of species intercepts to estimate.

B0.start

A matrix of starting values for B0.fixed.

C.fixed

A species-by-species matrix of interactions, indicating which interactions to estimate.

C.start

A matrix of starting values for C.fixed.

B.fixed

A matrix indicating which B coefficients (driver-species relationships) to estimate. Should have ncol(Y) columns and ncol(X) rows.

B.start

A matrix of starting values for B.fixed. Dimensions of B.start should match B.fixed.

sigma.fixed

Fixed value for the overall model variance. Use NA to estimate it from the model.

sigma.start

Starting value for estimating sigma.fixed.

dispersion.fixed

Fixed dispersion parameter for observation-level variation. A value of 1 corresponds to no over- or under-dispersion.

dispersion.start

Starting value for estimating dispersion.fixed.

V.fixed

A species-by-species covariance matrix representing environmental variation.

V.start

Starting values for V.fixed.

compute.information.matrix

Logical. If TRUE, computes the observed information matrix.

method

Optimization method. Acceptable values include "Nelder-Mead", "BFGS" (via optim), and "bobyqa" (via the minqa package).

optim.control

Optional list of control parameters passed to the optimizer. See the minqa package documentation for details.

maxit.optim

Maximum number of iterations for the optimizer (default is 1e+05). Increase if the optimizer needs more iterations.

hessian.method.args

A list of control parameters passed to the numerical Hessian calculator (e.g., numDeriv::hessian).

Value

An object of class "mnTS" containing estimated parameters.