confint_rob: Confidence Intervals for Model Parameters

In gragusa/ase: Collection of useful functions for "Applied Statistics and Econometrics"

Description

Computes confidence intervals for one or more parameters in a fitted model. There is a default and a method for objects inheriting from class "lm".

Usage

confint_rob(object, parm, level = 0.95, type = c("HC1", "const", "HC",
  "HC0", "HC2", "HC3", "HC4", "HC4m", "HC5"))

Arguments

object	a fitted model object.
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	the confidence level required.
type

Details

confint_rob assumes asymptotic normality of the estimators of the parameters for the fitted models, but does not assume conditional homoskedasticity.

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%).

Author(s)

Giuseppe Ragusa

gragusa/ase documentation built on May 17, 2019, 8:18 a.m.