This function removes model terms that do not improve the bootstrapped net residual improvement (NeRI) significantly.
bootstrapVarElimination_Res(object,
pvalue = 0.05,
Outcome = "Class",
data,
startOffset = 0,
type = c("LOGIT", "LM", "COX"),
testType = c("Binomial",
"Wilcox",
"tStudent",
"Ftest"),
loops = 64,
setIntersect = 1,
print=TRUE,
plots=TRUE
)
An object of the same class as object containing the reduced model
The number of loops it took for the model to stabilize
A list with the NeRI statistics of the reduced model, as given by the getVar.Res function
An object of class bootstrapValidation_Res containing the results of the bootstrap validation in the reduced model
An object of class formula with the formula used to fit the reduced model
The name of the last term that was removed (-1 if all terms were removed)
The model with close to minimum bootstrapped RMSE
The formula of the model before the FSC stage
the string formula of the model that had the minimum or close to minimum RMSE
An object of class lm, glm, or coxph containing the model to be analysed
The maximum p-value, associated to the NeRI, allowed for a term in the model
The name of the column in data that stores the variable to be predicted by the model
A data frame where all variables are stored in different columns
Only terms whose position in the model is larger than the startOffset are candidates to be removed
Fit type: Logistic ("LOGIT"), linear ("LM"), or Cox proportional hazards ("COX")
Type of non-parametric test to be evaluated by the improvedResiduals function: Binomial test ("Binomial"), Wilcoxon rank-sum test ("Wilcox"), Student's t-test ("tStudent"), or F-test ("Ftest")
The number of bootstrap loops
The intersect of the model (To force a zero intersect, set this value to 0)
Logical. If TRUE, information will be displayed
Logical. If TRUE, plots are displayed
Jose G. Tamez-Pena and Antonio Martinez-Torteya
For each model term \(x_i\), the residuals are computed for the Full model and the reduced model( where the term \(x_i\) removed). The term whose removal results in the smallest drop in bootstrapped test residuals improvement is selected. The hypothesis: the term improves residuals is tested by checking the p-value of average improvement. If \(p(residuals better than reduced residuals)>pvalue\), then the term is removed. In other words, only model terms that significantly aid in improving residuals are kept. The procedure is repeated until no term fulfils the removal criterion. The p-values of improvement can be computed via a sign-test (Binomial) a paired Wilcoxon test, paired t-test or f-test. The first three tests compare the absolute values of the residuals, while the f-test test if the variance of the residuals is improved significantly.
bootstrapVarElimination_Bin,
backVarElimination_Res,
bootstrapValidation_Res