# SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.stats.factor.implicitmodelpca

## Class ExplicitImplicitModelPCA

• java.lang.Object
• com.numericalmethod.suanshu.stats.factor.implicitmodelpca.ExplicitImplicitModelPCA
• Direct Known Subclasses:
AverageImplicitModelPCA

public class ExplicitImplicitModelPCA
extends Object
Given a time series of vectored observations, we decompose them into a reduced dimension of linear sum of both explicit/specified and implicit factors. The implicit factors are orthogonal. The user specifies the time series of observations and th explicit factor values over time. Specifically, we have $$R = Γ'G + \bar{R} + {B}'F + E$$ R is the time series of vectored observation. Its size is N x T. G is the time series of the explicit factor values. Its size is M x T, where M is the number of implicit factors. Γ' is the matrix of factor loadings for explicit factors. Its size is N x M. Each row is the explicit factor loadings for each subject. R_bar is the average of each subject's value over time, one entry per subject. It size is N. We copy the vector T times by columns to form a matrix for computation. F is the time series of the implicit factor values. Its size is K x T, where K is the number of implicit factors. B' is the matrix of implicit factor loadings. Its size is N x K. Each row is the implicit factor loadings for each subject. E is the residual matrix.
• ### Nested Class Summary

Nested Classes
Modifier and Type Class and Description
static class  ExplicitImplicitModelPCA.Result
• ### Constructor Summary

Constructors
Constructor and Description
ExplicitImplicitModelPCA(Matrix R, Matrix G, double varExplained)
ExplicitImplicitModelPCA(Matrix R, Matrix G, int K)
• ### Method Summary

All Methods
Modifier and Type Method and Description
ExplicitImplicitModelPCA.Result run()
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### ExplicitImplicitModelPCA

public ExplicitImplicitModelPCA(Matrix R,
Matrix G,
int K)
• #### ExplicitImplicitModelPCA

public ExplicitImplicitModelPCA(Matrix R,
Matrix G,
double varExplained)
• ### Method Detail

• #### run

public ExplicitImplicitModelPCA.Result run()