get_marginal_func: Get marginal functional covariance matrix
In jshamsho/LFBayes: Bayesian analysis of longitudinal and multidimensional functional data
Description
Usage
Arguments
Value
Examples
Description
Integrate over the longitudinal dimension to obtain an nt x nt marginal
covariance matrix
Usage
1
get_marginal_func(cov, ns, nt)
Arguments
cov
An ns*nt by ns*nt dimensional covariance matrix
ns
Number of longitudinal points
nt
Number of functional points
Value
An nt x nt marginal functional covariance matrix
Examples
1
See Root/Simulation
jshamsho/LFBayes documentation built on June 8, 2021, 4:38 a.m.
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Description Usage Arguments Value Examples
Description
Integrate over the longitudinal dimension to obtain an nt x nt marginal covariance matrix
Usage
1 | get_marginal_func(cov, ns, nt)
|
Arguments
cov |
An ns*nt by ns*nt dimensional covariance matrix |
ns |
Number of longitudinal points |
nt |
Number of functional points |
Value
An nt x nt marginal functional covariance matrix
Examples
1 | See Root/Simulation
|
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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