jacConfoundersComp: Jacobian for conditioning under compositionality
In CenterForStatistics-UGent/compIntegrate: Compositional omics model based visual integration
View source: R/jacConfoundersComp.R
jacConfoundersComp R Documentation
Jacobian for conditioning under compositionality
Description
Jacobian for conditioning under compositionality
Usage
jacConfoundersComp(
x,
confMat,
data,
meanVarTrend,
marginModel,
allowMissingness,
biasReduction,
subtractMax = TRUE
)
Arguments
x
the parameter estimates
confMat, data, meanVarTrend
arguments belonging to 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
CenterForStatistics-UGent/compIntegrate documentation built on Aug. 4, 2023, 1:08 p.m.
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View source: R/jacConfoundersComp.R
| jacConfoundersComp | R Documentation |
Jacobian for conditioning under compositionality
Description
Jacobian for conditioning under compositionality
Usage
jacConfoundersComp(
x,
confMat,
data,
meanVarTrend,
marginModel,
allowMissingness,
biasReduction,
subtractMax = TRUE
)
Arguments
x |
the parameter estimates |
confMat, data, meanVarTrend |
arguments belonging to 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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