| tpr.test {tpr} | R Documentation |
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 |
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 |
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 jun.yan@uconn.edu
References
Fine, Yan, and Kosorok (2004). Temporal Process Regression. Biometrika.
See Also
Examples
## see ?tpr