View source: R/forward.sel.par.R
forward.sel.par | R Documentation |
If Y is univariate, this function implements FS in regression. If Y is multivariate, this function implements FS using the F-test described by Miller and Farr (1971). This test requires that (i) the Y variables be standardized, and (ii) the error in the response variables be normally distributed (to be verified by the user).
forward.sel.par(
Y,
X,
alpha = 0.05,
K = nrow(X) - 1,
R2thresh = 0.99,
R2more = 0.001,
adjR2thresh = 0.99,
Yscale = FALSE,
verbose = TRUE
)
Y |
Response data matrix with n rows and m columns containing quantitative variables |
X |
Explanatory data matrix with n rows and p columns containing quantitative variables |
alpha |
Significance level. Stop the forward selection procedure if the p-value of a variable is higher than alpha. The default is 0.05 |
K |
Maximum number of variables to be selected. The default is one minus the number of rows |
R2thresh |
Stop the forward selection procedure if the R-square of the model exceeds the stated value. This parameter can vary from 0.001 to 1 |
R2more |
Stop the forward selection procedure if the difference in model R-square with the previous step is lower than R2more. The default setting is 0.001 |
adjR2thresh |
Stop the forward selection procedure if the adjusted R-square of the model exceeds the stated value. This parameter can take any value (positive or negative) smaller than 1 |
Yscale |
Standardize the variables in table Y to variance 1. The default setting is FALSE. The setting is automatically changed to TRUE if Y contains more than one variable. This is a validity condition for the parametric test of significance (Miller and Farr 1971) |
verbose |
If 'TRUE' more diagnostics are printed. The default setting is TRUE |
The forward selection will stop when either K, R2tresh, adjR2tresh, alpha and R2more has its parameter reached.
A dataframe with:
variables |
The names of the variables |
order |
The order of the selection of the variables |
R2 |
The R2 of the variable selected |
R2Cum |
The cumulative R2 of the variables selected |
AdjR2Cum |
The cumulative adjusted R2 of the variables selected |
F |
The F statistic |
pval |
The P-value statistic |
Pierre Legendre pierre.legendre@umontreal.ca and Guillaume Blanchet
Miller, J. K. & S. D. Farr. 1971. Bimultivariate redundancy: a
comprehensive measure of interbattery relationship. Multivariate
Behavioral Research, 6, 313–324.
x <- matrix(rnorm(30),10,3)
y <- matrix(rnorm(50),10,5)
forward.sel.par(y,x, alpha = 0.5)
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