truncMod: truncMod

In RAD: Fit RAD models to biological data

Description

truncMod fits a truncated negative bionomial model to data. Use to fit Species Richness (S\_i)

Usage

truncMod(trunc.form, trunc.pts, data, dist = 'NB', scale.covar=FALSE, est.var = TRUE, trace = TRUE)

Arguments

trunc.form	an object of class "formula" (or one that can be coerced to that class):a symbolic description of the model to be fitted. An offset in the form offset(log(area sampled)) should be included in the model formula to adjust for differences in area sampled between sites.
trunc.pts	A vector of truncation points of model. Must be of length equal to the numbers of rows(sites) of data. Set to N for fitting truncated species richness
data	a data frame containing the variables in the formula including the offset and the response. Each row should be a different site.
dist	one of either NB (negative binomial) or poission
scale.covar	Should the model matrix be scaled (TRUE/FALSE)? Useful if models do not converge. Setting this to TRUE will save the column means and sd for later prediction.
est.var	estimate the variance-covariance matrix using newton-raphson
trace	print model trace

Details

truncMod used glm.nb (MASS) or glm to get initial parameters for untruncated likelihoood & then uses nlminb to fit truncated model. Allows calculation of se for overdispersion parameter.

Value

coef	coefficents
vcov	variance-covariance matrix
logl	log-likelihood
AIC	AIC
residuals	model residuals, calculated using PIT
fitted	fitted values
sds	dfdf
sums	model sums
mean.X	column means for model matrix if scale.covar is TRUE
sd.X	column sds for model matrix if scale.covar is TRUE
formula	model formula

Authors

Piers Dunstan and Scott Foster

Examples

fish.data$N.scale <- fish.data$N/fish.data$area
S.form <- S~1 + N.scale + depth + O2_AV + temp_AV + offset(log(area))
model.S <- truncMod(S.form,fish.data$N,data=fish.data,est.var=TRUE,scale.covar=TRUE)
plot(model.S$fitted,model.S$residuals)
abline(h=0)

RAD documentation built on May 2, 2019, 9:36 a.m.