calculatePCA: Perform the principle component analysis using a correlation...
In smm52/timeBlocks: Converts Serial Measurement Data into Longitudinal Trajectory of Equally-sized Time Blocks
View source: R/responseScore.R
calculatePCA R Documentation
Perform the principle component analysis using a correlation matrix
Description
Perform the principle component analysis using a correlation matrix
Usage
calculatePCA(responseDf, responseColumns)
Arguments
responseDf
the data frame that contains the time blocks and the biomarker data per time block
responseColumn
names of the columns containing the patient block value for a biomarker (e.g. vector of string names). The score will be based only on these columns.
Value
the first principal component
smm52/timeBlocks documentation built on Nov. 27, 2022, 3:54 a.m.
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View source: R/responseScore.R
| calculatePCA | R Documentation |
Perform the principle component analysis using a correlation matrix
Description
Perform the principle component analysis using a correlation matrix
Usage
calculatePCA(responseDf, responseColumns)
Arguments
responseDf |
the data frame that contains the time blocks and the biomarker data per time block |
responseColumn |
names of the columns containing the patient block value for a biomarker (e.g. vector of string names). The score will be based only on these columns. |
Value
the first principal component
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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