Robust Breusch–Pagan test with bootstrap and effect sizes¶

Source: R/robust_implementations.R · Help: ?performBPTestRobust

Enhances performBPTest() by optionally studentising residuals, resampling the test statistic via bootstrap, and reporting effect sizes together with power diagnostics.

Usage¶

performBPTestRobust(
  model,
  data = NULL,
  studentize = TRUE,
  bootstrap = FALSE,
  B = 999,
  ci_level = 0.95,
  parallel = FALSE,
  studentized
)

Arguments¶

model: A fitted stats::lm object describing the mean structure whose residual variance is to be assessed.
data: A base::data.frame (or compatible object) containing the variables referenced in model. The data must include all observations used to fit model and should not contain unresolved missing values. When NULL, the default, the model frame of model is used. It holds the terms of the model rather than its variables (log(x) rather than x), so a model that transforms a variable needs data, as does a model with an offset() term, and so may a fit whose weights or offset argument is a column of the data, which the model frame holds as (weights) or (offset).
studentize: Logical, use studentized residuals for the auxiliary regression (Koenker variant)? Defaults to TRUE. The name matches lmtest::bptest() and performHarveyTest().
bootstrap: Logical, compute bootstrap diagnostics for the statistic and p-value? The bootstrap is bootstrapTestStatistic(), so on a fit returned by fitWLS() each replicate estimates the weights again, its default since 0.15.0. There is no argument to hold them fixed here; bootstrapTestStatistic() with reestimate_weights = FALSE does that.
B: Number of bootstrap replications when bootstrap = TRUE. Defaults to 999, at which a bootstrap p-value of the form (1 + #) / (B + 1) gives an exact test at the 5% and 1% levels; it was 1000 before 0.15.0. The value is recorded in robust_details$bootstrap$B whether or not the bootstrap runs.
ci_level: Confidence level for reported intervals.
parallel: Logical, allow parallel bootstrap evaluation when the parallel package is available. A seeded call gives the same result each time; see Parallel replicates in bootstrapTestStatistic().
studentized: Deprecated since 0.15.0: use studentize. It is still accepted, with a warning, and does what studentize does; it stops working in 1.0.0.

Value¶

An augmented htest object containing a robust_details element describing the additional diagnostics. Its studentized field records the value of studentize.

Details¶

Offers expanded reporting for the Breusch–Pagan family of tests including bootstrap p-values and asymptotic confidence intervals. The optional studentize argument toggles between the classic and Koenker versions.

References¶

Breusch, T. S., & Pagan, A. R. (1979). A simple test for heteroscedasticity and random coefficient variation. Econometrica, 47(5), 1287–1294.

Koenker, R. (1981). A note on studentizing a test for heteroscedasticity. Journal of Econometrics, 17(1), 107–112.

Examples¶

data(mtcars)
mod <- lm(mpg ~ wt + qsec, data = mtcars)
performBPTestRobust(mod, mtcars, bootstrap = TRUE, B = 200)