confint.lmstar: Compute asymptotic confidence intervals for STAR linear...

In countSTAR: Flexible Modeling of Count Data

Compute asymptotic confidence intervals for STAR linear regression

Description

For a linear regression model within the STAR framework, compute (asymptotic) confidence intervals for a regression coefficient of interest. Confidence intervals are computed by inverting the likelihood ratio test and profiling the log-likelihood.

Usage

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

Arguments

object	Object of class "lmstar" as output by lm_star
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	confidence level; default is 0.95
...	Ignored

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

Examples

#Simulate data with count-valued response y:
sim_dat = simulate_nb_lm(n = 100, p = 2)
y = sim_dat$y; X = sim_dat$X

#Select a transformation:
transformation = 'np'

#Estimate model
fit = lm_star(y~X, transformation=transformation)

#Confidence interval for all parameters
confint(fit)

countSTAR documentation built on July 9, 2023, 5:12 p.m.