apca: Asymptotic Principal Component Analysis
In d-/MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models
apca R Documentation
Asymptotic Principal Component Analysis
Description
Perform asymptotic PCA for a data set. Typically for cases in which
the number of variables is greater than the number of data points.
Usage
apca(da, m)
Arguments
da
A T-by-k data set matrix, where T is the sample size and k is the
dimension
m
The number of common factors
Details
Perform the PCA analysis of interchanging the roles of variables and observations.
Value
sdev
Square root of the eigenvalues
factors
The common factors
loadings
The loading matrix
Author(s)
Ruey S. Tsay
References
Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.
Examples
rtn=matrix(rnorm(1200),12,100)
sp100=apca(rtn,3)
d-/MTS documentation built on June 12, 2022, 12:50 a.m.
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| apca | R Documentation |
Asymptotic Principal Component Analysis
Description
Perform asymptotic PCA for a data set. Typically for cases in which the number of variables is greater than the number of data points.
Usage
apca(da, m)
Arguments
da |
A T-by-k data set matrix, where T is the sample size and k is the dimension |
m |
The number of common factors |
Details
Perform the PCA analysis of interchanging the roles of variables and observations.
Value
sdev |
Square root of the eigenvalues |
factors |
The common factors |
loadings |
The loading matrix |
Author(s)
Ruey S. Tsay
References
Tsay (2014, Chapter 6). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.
Examples
rtn=matrix(rnorm(1200),12,100) sp100=apca(rtn,3)
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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