Last data update: 2014.03.03
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R: Significance and Goodness-of-fit Test of TPR
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
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chypo |
hypothesized value of coefficients
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idx |
the index of the coefficients to be tested
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weight |
whether or not use inverse variation weight
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ncut |
the number of cuts of the interval of interest in
integral test
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cfitList |
a list of fitted object from cst.fit.ff
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nsim |
the number of bootstrap samples in bootstrap test
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plot |
whether or not plot
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fit1 |
fit of H0 model (reduced)
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fit2 |
fit of H1 model (full)
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p |
the index of the time-varying estimation in fit2
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q |
the index of the time-independent estimation in fit1
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Value
Test statistics and their p-values.
Author(s)
Jun Yan jyan@stat.uconn.edu
References
Fine, Yan, and Kosorok (2004). Temporal Process Regression. Biometrika.
See Also
tpr
Examples
## see ?tpr
Results
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