VGAMdata: oapospoisson – R documentation

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oapospoisson

One-Altered Positive-Poisson Distribution

Description

Fits a one-altered positive-Poisson distribution based on a conditional model involving a Bernoulli distribution and a 1-truncated positive-Poisson distribution.

Usage

oapospoisson(lpobs1 = "logitlink", llambda = "loglink",
             type.fitted = c("mean", "lambda", "pobs1", "onempobs1"),
             ipobs1 = NULL, zero = NULL)

Arguments

`lpobs1`	Link function for the parameter pobs1 or phi, called `pobs1` or `phi` here. See `Links` for more choices.
`llambda`	See `pospoisson` for details.
`type.fitted`	See `CommonVGAMffArguments` and `fittedvlm` for information.
`ipobs1, zero`	See `CommonVGAMffArguments` for information.

Details

The response Y is one with probability pobs1, or Y has a 1-truncated positive-Poisson distribution with probability 1-pobs1. Thus 0 < pobs1 < 1, which is modelled as a function of the covariates. The one-altered positive-Poisson distribution differs from the one-inflated positive-Poisson distribution in that the former has ones coming from one source, whereas the latter has ones coming from the positive-Poisson distribution too. The one-inflated positive-Poisson distribution is implemented in the VGAM package. Some people call the one-altered positive-Poisson a hurdle model.

The input can be a matrix (multiple responses). By default, the two linear/additive predictors of oapospoisson are (logit(phi), log(lambda))^T.

Value

An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, and vgam.

The fitted.values slot of the fitted object, which should be extracted by the generic function fitted, returns the mean mu (default) which is given by

mu = phi + (1- phi) A

where A is the mean of the one-truncated positive-Poisson distribution. If type.fitted = "pobs1" then pobs1 is returned.

Note

This family function effectively combines binomialff and otpospoisson into one family function.

Author(s)

T. W. Yee

Examples

## Not run: odata <- data.frame(x2 = runif(nn <- 1000))
odata <- transform(odata, pobs1  = logitlink(-1 + 2*x2, inverse = TRUE),
                          lambda =  loglink( 1 + 1*x2, inverse = TRUE))
odata <- transform(odata, y1 = roapospois(nn, lambda = lambda, pobs1 = pobs1),
                          y2 = roapospois(nn, lambda = lambda, pobs1 = pobs1))
with(odata, table(y1))

ofit <- vglm(cbind(y1, y2) ~ x2, oapospoisson, data = odata, trace = TRUE)
coef(ofit, matrix = TRUE)
head(fitted(ofit))
head(predict(ofit))
summary(ofit)

## End(Not run)

VGAMdata

Data Supporting the 'VGAM' Package

v1.1-5

GPL-2

Authors

Thomas Yee [aut, cre, cph], James Gray [dtc]

Initial release

2021-01-13