confint.cmp: Confidence Intervals for CMP Model Parameters

In mpcmp: Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression

Description

Computes confidence intervals for one or more parameters in a fitted model.

Usage

## S3 method for class 'cmp'
confint(object, parm, level = 0.95, ...)

Arguments

object	an object class 'cmp', obtained from a call to glm.cmp.
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names (comparing to those provided by coef()) . If missing, all parameters are considered.
level	the confidence level required.
...	other arguments passed to or from other methods (currently unused).

Value

A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in % (by default 2.5% and 97.5%).

Examples

data(attendance)
M.attendance <- glm.cmp(daysabs~ gender+math+prog, data=attendance)
confint(M.attendance)
confint(M.attendance, parm = "math", level = 0.9)

mpcmp documentation built on Oct. 26, 2020, 9:07 a.m.