View source: R/functions_gofLMM.R
gof.lmm.O.type2.boot | R Documentation |
Goodness-of fit test based on cumulative sum stochastic process for Oi and John's idea using full parametric bootstrap to obtain p-values. Not well tested!
gof.lmm.O.type2.boot( fit, residuals = c("individual", "cluster"), std.type = c(1, 2), use.correction.for.imbalance = FALSE, type = c("sign.flip", "permutation"), M = 100, B = 100, order.by.original = FALSE, verbose = FALSE )
fit |
The result of a call to |
residuals |
Residuals to be used when constructing the process. Possible values are |
std.type |
Type of standardization to be used for the residuals when constructing the process.
Currently implemeneted options are |
use.correction.for.imbalance |
Logical. use $n_i^-1/2 S_i$ when standardizing the residuals. Defaults to |
type |
How to obtain the processes $W^m$. Possible values are |
M |
Number of random simulations/sign-flipps/permutations. Defaults to |
B |
Number of boot replications. Defaults to |
order.by.original |
Logical. Should the residuals in the the processes $W^m$ be ordered by the original fitted values? Defaults to |
verbose |
Logical. Print the current status of the test. Can slow down the algorithm, but it can make it feel faster. Defaults to |
An object of class "gofLMM"
for which plot
and summary
functions are available.
Rok Blagus, rok.blagus@mf.uni-lj.si
gof.lmm.pan
, gof.lmm.sim
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