noCovariatesAI: Variance component estimation without covariates using...
In xzhoulab/SPARK: Spatial Pattern Recognition via Kernels
noCovariatesAI R Documentation
Variance component estimation without covariates using Average Information algorithm, float format
Description
Variance component estimation without covariates using Average Information algorithm, float format
Usage
noCovariatesAI(Yin, Xin, Din, tauin, fixtauin, tolin)
Arguments
Yin
Working vector
Xin
Covariate matrix
Din
Weight for each gene
tauin
Initial value for variance component
fixtauin
Variance component to be optimized
tolin
Tolerance
Value
A list
xzhoulab/SPARK documentation built on Nov. 20, 2022, 2:54 p.m.
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| noCovariatesAI | R Documentation |
Variance component estimation without covariates using Average Information algorithm, float format
Description
Variance component estimation without covariates using Average Information algorithm, float format
Usage
noCovariatesAI(Yin, Xin, Din, tauin, fixtauin, tolin)
Arguments
Yin |
Working vector |
Xin |
Covariate matrix |
Din |
Weight for each gene |
tauin |
Initial value for variance component |
fixtauin |
Variance component to be optimized |
tolin |
Tolerance |
Value
A list
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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