Principal Component Analysis with Orthogonal Instrumental Variables
PCAoiv(X, Z, row.w = NULL, ncp = 5)
data frame with only numeric variables
data frame of instrumental variables to be "partialled out"", which can be numeric or factors. It must have the same number of rows as
Numeric vector of row weights. If NULL (default), a vector of 1 for uniform row weights is used.
number of dimensions kept in the results (by default 5)
Principal Component Analysis with Orthogonal Instrumental Variables consists in two steps :
1. Computation of one linear regression for each variable in
X, with this variable as response and all variables in
Z as explanatory variables.
2. Principal Component Analysis of the set of residuals from the regressions in 1.
An object of class
FactoMineR package, and an additional item :
the share of inertia not explained by the instrumental variables
Bry X., 1996, Analyses factorielles multiples, Economica.
Lebart L., Morineau A. et Warwick K., 1984, Multivariate Descriptive Statistical Analysis, John Wiley and sons, New-York.)