tpr.test: Significance and Goodness-of-fit Test of TPR

In tpr: Temporal Process Regression

Significance and Goodness-of-fit Test of TPR

Description

Two kinds of tests are provided for inference on the coefficients in a fully functional TRP model: integral test and bootstrap test.

Usage

sig.test.int.ff(fit, chypo = 0, idx, weight = TRUE, ncut = 2)
sig.test.boots.ff(fit, chypo = 0, idx, nsim = 1000, plot = FALSE)
gof.test.int.ff(fit, cfitList = NULL, idx, weight = TRUE, ncut = 2)
gof.test.boots.ff(fit, cfitList = NULL, idx, nsim = 1000, plot = FALSE)
gof.test.boots.pf(fit1, fit2, nsim, p = NULL, q = 1)

Arguments

fit	a fitted object from tpr
chypo	hypothesized value of coefficients
idx	the index of the coefficients to be tested
weight	whether or not use inverse variation weight
ncut	the number of cuts of the interval of interest in integral test
cfitList	a list of fitted object from cst.fit.ff
nsim	the number of bootstrap samples in bootstrap test
plot	whether or not plot
fit1	fit of H0 model (reduced)
fit2	fit of H1 model (full)
p	the index of the time-varying estimation in fit2
q	the index of the time-independent estimation in fit1

Value

Test statistics and their p-values.

Author(s)

Jun Yan [e-mail]

References

Fine, Yan, and Kosorok (2004). Temporal Process Regression. Biometrika.

See Also

tpr

Examples

## see ?tpr

tpr documentation built on Oct. 17, 2022, 9:07 a.m.