prepare_mfpca: Prepare Information Necessary for MFPCA
In multifamm: Multivariate Functional Additive Mixed Models
Description
This is an internal function contained in the multiFAMM function. This step
uses the information from the univariate FLMMs for the MFPCA. It also allows
a simple weighting scheme of the MFPCA.
Usage
1
prepare_mfpca(model_list, fRI_B, mfpc_weight)
Arguments
model_list
List containing sparseFLMM objects for each dimension as
given by the output of apply_sparseFLMM()
fRI_B
Boolean for including functional random intercept for individual
(B in Cederbaum). Defaults to FALSE.
mfpc_weight
TRUE if the estimated univariate error variance is to be
used as weights in the scalar product of the MFPCA.
multifamm documentation built on Sept. 28, 2021, 9:07 a.m.
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Description
This is an internal function contained in the multiFAMM function. This step uses the information from the univariate FLMMs for the MFPCA. It also allows a simple weighting scheme of the MFPCA.
Usage
1 | prepare_mfpca(model_list, fRI_B, mfpc_weight)
|
Arguments
model_list |
List containing sparseFLMM objects for each dimension as given by the output of apply_sparseFLMM() |
fRI_B |
Boolean for including functional random intercept for individual
(B in Cederbaum). Defaults to |
mfpc_weight |
TRUE if the estimated univariate error variance is to be used as weights in the scalar product of the MFPCA. |
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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