confintvglm {VGAM} | R Documentation

## Confidence Intervals for VGLM Parameters

### Description

Computes confidence intervals for one or more parameters in a fitted model. Currently the object must be a `"vglm"` object.

### Usage

    confint(object, parm, level = 0.95, ...)

### Arguments

`object` | A fitted model object.
`parm, level, ...` | Same as `confint`.

### Details

This methods function is based on `confint.default` and assumes asymptotic normality. In particular, the `coef` and `vcov` methods functions are used for `vglm-class` objects. Unlike for `glm` objects, there is no profiling currently implemented.

For `rrvglm-class` objects, currently an error message is produced because I haven't gotten around to write the methods function; it's not too hard, but am too busy! An interim measure is to coerce the object into a `"vglm"` object, but then the confidence intervals will tend to be too narrow because the estimated constraint matrices are treated as known.

For `vgam-class` objects, currently an error message is produced because the theory is undeveloped.

### Value

Same as `confint`.

### Author(s)

Thomas W. Yee

### See Also

`vcovvlm`, `summaryvglm`, `confint`.

### Examples

    # Example 1: this is based on a glm example
    counts <- c(18,17,15,20,10,20,25,13,12)
    outcome <- gl(3, 1, 9); treatment <- gl(3, 3)
     glm.D93 <-  glm(counts ~ outcome + treatment, family = poisson())
    vglm.D93 <- vglm(counts ~ outcome + treatment, family = poissonff)
    confint(glm.D93) # needs MASS to be present on the system
    confint.default(glm.D93)  # based on asymptotic normality
    confint(vglm.D93)
    confint(vglm.D93) - confint(glm.D93)    # Should be all 0s
    confint(vglm.D93) - confint.default(glm.D93)  # based on asymptotic normality

    # Example 2: simulated negative binomial data with multiple responses
    ndata <- data.frame(x2 = runif(nn <- 300))
    ndata <- transform(ndata, y1 = rnbinom(nn, mu = exp(3+x2), size = exp(1)),
                              y2 = rnbinom(nn, mu = exp(2-x2), size = exp(0)))
    fit1 <- vglm(cbind(y1, y2) ~ x2, negbinomial, data = ndata, trace = TRUE)
    coef(fit1, matrix = TRUE)
    confint(fit1)
    confint(fit1, "x2:1")  #  This might be improved to "x2" some day...
    fit2 <- rrvglm(y1 ~ x2, negbinomial(zero = NULL), data = ndata)
    confint(as(fit2, "vglm"))  # Too narrow (SEs are biased downwards)

[Package VGAM version 1.0-1 Index]