prabclus (version 2.2-2)

prab.sarestimate: Estimates SAR model from log-abundance matrix of prab-object.

Description

This is either an interface for the function errorsarlm for abundance data stored in an object of class prab implemented for use in abundtest, or, in case that spatial information should be ignored, it estimates a two-way additive unreplicated linear model for log-abundances on factors species and region.

Usage

prab.sarestimate(abmat, prab01=NULL,sarmethod="eigen",
                             weightstyle="C",
                             quiet=TRUE, sar=TRUE,
                             add.lmobject=TRUE)

Arguments

abmat

object of class prab.

prab01

presence-absence matrix of same dimensions than the abundance matrix of prabobj. This specifies the presences and absences on which the presence/absence step of abundance-based tests is based (see details). If NULL (which i

sarmethod

this is passed on as parameter method to errorsarlm and documented there. We don't have experience with any other choice than "eigen".

weightstyle

can take values "W", "B", "C", "U", and "S" though tests suggest that "C" should be chosen. See nb2listw.

quiet

this is passed on as parameter quiet to errorsarlm and documented there.

sar

logical. If TRUE, a simultaneous autoregression model is fitted by calling errorsarlm. If FALSE, a two-way additive unreplicated linear model for log-abunda

add.lmobject

logical. If TRUE, the whole output object of errorsarlm (or lm) is given out.

Value

• A list with the following components:
• sar
  see above.
• intercept
  numeric. Estimator of the intercept.
• sigma
  numeric. Estimator of error standard deviation.
• regeffects
  numeric vector. Estimator for region effects.
• speceffects
  numeric vector. Estimator for species effects.
• lamda
  numeric. Governs the degree of spatial autocorrelation. See errorsarlm.
• size
  integer. Length of neighborhood list generated by nb2listw used by errorsarlm.
• nbweight
  numeric. Average weight of neighbors.
• lmobject
  if add.lmobject=TRUE, output object of either lm or errorsarlm.

See Also

errorsarlm, abundtest

Examples

data(siskiyou)
  x <- prabinit(prabmatrix=siskiyou, neighborhood=siskiyou.nb,
             distance="none")
#  Not run; this needs package spdep 
#  prab.sarestimate(x)
  prab.sarestimate(x, sar=FALSE)