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The goal of infotest is to implement the Cameron & Trivedi (1990) Information Matrix test for regression models, decomposing it into tests of heteroskedasticity, skewness, and kurtosis. ## Installation
You can install the development version of infotest like so:
install.packages("pak")
pak::pkg_install("guliyevh/infotest")This is a basic example which shows you how to solve a common problem:
library(infotest)
# Fit a simple linear model
model <- lm(Sepal.Length ~ Sepal.Width + Petal.Length, data = iris)
# Run the Cameron & Trivedi (1990) IM test decomposition
infotest(model)
White's (1980) heteroskedasticity test
H0: Homoskedasticity
Ha: Unrestricted heteroskedasticity
chi2(5) = 16.3799
Prob > chi2 = 0.0058
Cameron & Trivedi's (1990) decomposition of IM-test
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Source chi2 df p
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Heteroskedasticity 16.38 5 0.0058
Skewness 0.15 2 0.9273
Kurtosis 0.49 1 0.4834
Joint Test 17.02 8 0.0299
----------------------------------------
# Without White's (1980) heteroskedasticity test
infotest(model, white = FALSE)
Cameron & Trivedi's (1990) decomposition of IM-test
----------------------------------------
Source chi2 df p
----------------------------------------
Heteroskedasticity 16.38 5 0.0058
Skewness 0.15 2 0.9273
Kurtosis 0.49 1 0.4834
Joint Test 17.02 8 0.0299
----------------------------------------Cameron, A. C., & Trivedi, P. K. (1990). The information matrix test and its applied alternatives. Econometric Theory, 6(2), 179–195.
White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838.
If you use this package, please cite:
Hasraddin Guliyev (2025). infotest: Information Matrix Test for Regression Models. R package version 0.1.0.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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