multinomPois: Multinomial-Poisson Mixtures
In ianfiske/unmarked: Models for Data from Unmarked Animals

Description Usage Arguments Details Value Author(s) References See Also Examples

Fit the multinomial-Poisson abundance mixture model.

1 2	multinomPois(formula, data, starts, method = "BFGS", control = list(), se = TRUE)

`formula`	double right-hand side formula for detection and abundance covariates, in that order.
`data`	unmarkedFrame supplying data.
`starts`	vector of starting values.
`method`	Optimization method used by `optim`.
`control`	Other arguments passed to `optim`.
`se`	logical specifying whether or not to compute standard errors.

This function takes advantage of the closed form of the integrated likelihood when a latent Poisson distribution is assumed for abundance at each site and a multinomial distribution is taken for the observation state. Many common sampling methods can be framed in this context. For example, double-observer point counts, removal sampling, and distance sampling can all be analyzed with this function by specifying the proper multinomial cell probablilities. This is done with by supplying the appropriate function (piFun) argument. removalPiFun and doublePiFun are supplied as example cell probability functions.

unmarkedFit object describing the model fit.

Ian Fiske

Royle, J. A., Dawson, D., & Bates, S. (2004). Modeling abundance effects in distance sampling. Ecology, 85(6), 1591-1597.

Royle, J. A. (2004). Generalized estimators of avian abundance from count survey data. Animal Biodiversity and Conservation, 27(1), 375-386.

Royle, J. A., & Dorazio, R. M. (2006). Hierarchical Models of Animal Abundance and Occurrence. Journal Of Agricultural Biological And Environmental Statistics, 11(3), 249.

piFuns

data(ovendata)
ovenFrame <- unmarkedFrameMPois(ovendata.list$data,
siteCovs=as.data.frame(scale(ovendata.list$covariates[,-1])), type = "removal")
(fm1 <- multinomPois(~ 1 ~ ufp + trba, ovenFrame))
(fm2 <- multinomPois(~ 1 ~ ufp, ovenFrame))
(fm3 <- multinomPois(~ 1 ~ trba, ovenFrame))
(fm4 <- multinomPois(~ 1 ~ 1, ovenFrame))
fmList <- fitList(Global=fm1, ufp=fm2, trba=fm3, Null=fm4)

# Model selection
modSel(fmList, nullmod="Null")