glpls1a
(Package: gpls) :
Fit IRWPLS and IRWPLSF model
Fit Iteratively ReWeighted Least Squares (IRWPLS) with an option of Firth's bias reduction procedure (IRWPLSF) for two-group classification
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a
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glpls1a.cv.error
(Package: gpls) :
Leave-one-out cross-validation error using IRWPLS and IRWPLSF model
Leave-one-out cross-validation training set classification error for fitting IRWPLS or IRWPLSF model for two group classification
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a.cv.error
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glpls1a.logit.all
(Package: gpls) :
Fit MIRWPLS and MIRWPLSF model separately for logits
Apply Iteratively ReWeighted Least Squares (MIRWPLS) with an option of Firth's bias reduction procedure (MIRWPLSF) for multi-group (say C+1 classes) classification by fitting logit models for all C classes vs baseline class separately.
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a.logit.all
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glpls1a.mlogit
(Package: gpls) :
Fit MIRWPLS and MIRWPLSF model
Fit multi-logit Iteratively ReWeighted Least Squares (MIRWPLS) with an option of Firth's bias reduction procedure (MIRWPLSF) for multi-group classification
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a.mlogit
●
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glpls1a.mlogit.cv.error
(Package: gpls) :
Leave-one-out cross-validation error using MIRWPLS and MIRWPLSF model
Leave-one-out cross-validation training set error for fitting MIRWPLS or MIRWPLSF model for multi-group classification
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a.mlogit.cv.error
●
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glpls1a.train.test.error
(Package: gpls) :
out-of-sample test set error using IRWPLS and IRWPLSF model
Out-of-sample test set error for fitting IRWPLS or IRWPLSF model on the training set for two-group classification
● Data Source:
BioConductor
● Keywords: regression
● Alias: glpls1a.train.test.error
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gpls
(Package: gpls) :
A function to fit Generalized partial least squares models.
Partial least squares is a commonly used dimension reduction technique. The paradigm can be extended to include generalized linear models in several different ways. The code in this function uses the extension proposed by Ding and Gentleman, 2004.
● Data Source:
BioConductor
● Keywords: classif
● Alias: gpls, gpls.default, gpls.formula, print.gpls
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predict.gpls
(Package: gpls) :
A prediction method for gpls.
A simple prediction method for gpls objects.
● Data Source:
BioConductor
● Keywords: classif
● Alias: predict,gpls-method, predict.gpls
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