functional_ICC_bootstrap: Functional Intraclass Correlation Bootstrap
In dsenturk/mhpca: Multilevel Hybrid Principal Components Analysis
Description
Usage
Arguments
Value
Description
Functional Intraclass Correlation Bootstrap
Usage
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functional_ICC_bootstrap(
MHPCA,
nboots,
alpha = 0.05,
maxiter,
epsilon,
fve_cutoff,
nknots,
quiet = FALSE,
file_name = NULL
)
Arguments
MHPCA
MHPCA object
nboots
number of bootstraps to perform
alpha
alpha level
maxiter
maximum iterations
epsilon
epsilon for MM algorithm
fve_cutoff
fraction of variance cutoff for M-HPCA
nknots
number of knots for splines
quiet
logical for printing timing messages
file_name
name of file to save individual bootstrapped results in if desired
Value
fICC percentiles (data.frame)
dsenturk/mhpca documentation built on Dec. 20, 2021, 2:11 a.m.
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Description Usage Arguments Value
Description
Functional Intraclass Correlation Bootstrap
Usage
1 2 3 4 5 6 7 8 9 10 11 | functional_ICC_bootstrap(
MHPCA,
nboots,
alpha = 0.05,
maxiter,
epsilon,
fve_cutoff,
nknots,
quiet = FALSE,
file_name = NULL
)
|
Arguments
MHPCA |
MHPCA object |
nboots |
number of bootstraps to perform |
alpha |
alpha level |
maxiter |
maximum iterations |
epsilon |
epsilon for MM algorithm |
fve_cutoff |
fraction of variance cutoff for M-HPCA |
nknots |
number of knots for splines |
quiet |
logical for printing timing messages |
file_name |
name of file to save individual bootstrapped results in if desired |
Value
fICC percentiles (data.frame)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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