R-Studio
Write a generic R function of white test. It takes a fit of linear model and outputs the value of white statistics, degree of freedom, and p-value for the hypothesis testing of constant-variance assumption. It should be similar to bptest as in lmtest package.
> mdl = lm(final ~ midterm, data = stat500) > bptest(mdl) studentized Breusch-Pagan test data: mdl BP = 0.86813, df = 1, p-value = 0.3515 > bptest(mdl, studentize = FALSE) Breusch-Pagan test data: mdl BP = 0.67017, df = 1, p-value = 0.413 > ncvTest(mdl) Non-constant Variance Score Test Variance formula: ~ fitted.values Chisquare = 0.6701721 Df = 1 p = 0.4129916 > > n = nrow(stat500) > e = residuals(mdl) > bpmdl = lm(e^2 ~ midterm, data = stat500) > lambda = (n - 1) / n * var(e^2) / (2 * ((n - 1) / n * var(e))^2) > Studentized_bp = n * summary(bpmdl)$r.squared > Original_bp = Studentized_bp * lambda > > Studentized_bp [1] 0.8681335 > Original_bp [1] 0.6701721
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