logLikelihood: Compute log-likelihood for aggregated model
In gabrielfranco89/aggrmodel: A R package to fit aggregated data model
Description
Usage
Arguments
Value
View source: R/likelihoodFunctions.R
Description
Compute log-likelihood for aggregated model
Usage
1
logLikelihood(data, muVec, covMtxList, doPar = FALSE, nc = NULL)
Arguments
data
Data Frame with 4 columns in the following order: Group, Replicates, Time, Signal
muVec
Vector Xβ of fitted values
covMtxList
List of covariance matrices for each group
doPar
TRUE/FALSE if computation should be parallel
nc
Number of clusters. Default: parallel::detectCores()
Value
Log-likehood value
gabrielfranco89/aggrmodel documentation built on June 1, 2020, 8:57 a.m.
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Description Usage Arguments Value
View source: R/likelihoodFunctions.R
Description
Compute log-likelihood for aggregated model
Usage
1 | logLikelihood(data, muVec, covMtxList, doPar = FALSE, nc = NULL)
|
Arguments
data |
Data Frame with 4 columns in the following order: Group, Replicates, Time, Signal |
muVec |
Vector Xβ of fitted values |
covMtxList |
List of covariance matrices for each group |
doPar |
TRUE/FALSE if computation should be parallel |
nc |
Number of clusters. Default: parallel::detectCores() |
Value
Log-likehood value
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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