jacConfoundersComp: Jacobian for conditioning under compositionality
In combi: Compositional omics model based visual integration
Description
Usage
Arguments
Value
View source: R/jacConfoundersComp.R
Description
Jacobian for conditioning under compositionality
Usage
1
2
jacConfoundersComp(x, confMat, data, meanVarTrend, marginModel,
allowMissingness, biasReduction, subtractMax = TRUE)
Arguments
x
the parameter estimates
confMat
Characteristics of the views
data
Characteristics of the views
meanVarTrend
Characteristics of the views
marginModel, biasReduction, subtractMax
The marginal mode, and booleans
indicating bias reduction and maximum subtraction
allowMissingness
a boolean, should missing values be allowed
Value
the jacobian matrix
combi documentation built on Nov. 8, 2020, 5:34 p.m.
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Description Usage Arguments Value
View source: R/jacConfoundersComp.R
Description
Jacobian for conditioning under compositionality
Usage
1 2 | jacConfoundersComp(x, confMat, data, meanVarTrend, marginModel,
allowMissingness, biasReduction, subtractMax = TRUE)
|
Arguments
x |
the parameter estimates |
confMat |
Characteristics of the views |
data |
Characteristics of the views |
meanVarTrend |
Characteristics of the views |
marginModel, biasReduction, subtractMax |
The marginal mode, and booleans indicating bias reduction and maximum subtraction |
allowMissingness |
a boolean, should missing values be allowed |
Value
the jacobian matrix
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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