pcalogit_perf: Classification logistic model for simulated dataset of DMPs...
In genomaths/MethylIT: Methylation Analysis Based on Signal Detection
pcalogit_perf R Documentation
Classification logistic model for simulated dataset of DMPs used in examples
Description
This data/object carries the information about the classification performance
of the combined models of Principal Components PCA and logistic
regression analyses on the set of dmps.
Usage
pcalogit_perf
Format
pcalogit_perf is an object from class "pcaLogisticR",
consisting of a list with the following elements:
- Performance
Classification performance of the
"pca.logistic" model on the set of dmps
.
- FDR
False discovery rate estimated for the logistic
model on the set of dmps
- model
The fitted glm
"logistic" and the "PCA" models. The "PCA" is fitted
with prcomp
function.
pcalogit_perf is an object from "pcaLogisticR" class,
which was obtained applying evaluateDIMPclass function on the
set of dmps.
genomaths/MethylIT documentation built on Feb. 3, 2024, 1:24 a.m.
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| pcalogit_perf | R Documentation |
Classification logistic model for simulated dataset of DMPs used in examples
Description
This data/object carries the information about the classification performance
of the combined models of Principal Components PCA and logistic
regression analyses on the set of dmps.
Usage
pcalogit_perf
Format
pcalogit_perf is an object from class "pcaLogisticR", consisting of a list with the following elements:
- Performance
Classification performance of the "pca.logistic" model on the set of
dmps
.
- FDR
False discovery rate estimated for the logistic model on the set of
dmps- model
The fitted
glm"logistic" and the "PCA" models. The "PCA" is fitted withprcomp
function.
pcalogit_perf is an object from "pcaLogisticR" class,
which was obtained applying evaluateDIMPclass function on the
set of dmps.
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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