vim.individual: VIM for Inputs

In holgerschw/logicFS: Identification of SNP Interactions

Description

Quantifies the importance of each input variable occuring in at least one of the logic regression models found in the application of logic.bagging.

Usage

vim.input(object, useN = NULL, iter = NULL, prop = TRUE,
   standardize = NULL, mu = 0, addMatImp = FALSE, 
   prob.case = 0.5, rand = NA)

Arguments

object	an object of class logicBagg, i.e.\ the output of logic.bagging
useN	logical specifying if the number of correctly classified out-of-bag observations should be used in the computation of the importance measure. If FALSE, the proportion of correctly classified oob observations is used instead. If NULL (default), then the specification of useN in object is used.
iter	integer specifying the number of times the values of the considered variable are permuted in the computation of its importance. If NULL (default), the values of the variable are not permuted, but the variable is removed from the model.
prop	should the proportion of logic regression models containing the respective variable also be computed?
standardize	should a standardized version of the importance measure for a set of variables be returned? By default, standardize = TRUE is used in the classification and the (multinomial) logistic regression case, and standarize is set to FALSE in the linear regression case. For details, see mu.
mu	a non-negative numeric value. Ignored if standardize = FALSE. Otherwise, a t-statistic for testing the null hypothesis that the importance of the respective variable is equal to mu is computed.
addMatImp	should the matrix containing the improvements due to each of the variables in each of the logic regression models be added to the output?
prob.case	a numeric value between 0 and 1. If the logistic regression approach of logic regression has been used in logic.bagging, then an observation will be classified as a case (or more exactly, as 1), if the class probability of this observation is larger than prob.case. Otherwise, prob.case is ignored.
rand	an integer for setting the random number generator in a reproducible case.

Value

An object of class logicFS containing

vim	the importances of the variables,
prop	the proportion of logic regression models containing the respective variable (if prop = TRUE) or NULL (if prop = FALSE),
primes	the names of the variables,
type	the type of model (1: classification, 2:linear regression, 3: logistic regression),
param	further parameters (if addInfo = TRUE in the previous call of logic.bagging),
mat.imp	either a matrix containing the improvements due to the variables for each of the models (if addMatImp = TRUE), or NULL (if addMatImp = FALSE),
measure	the name of the used importance measure,
useN	the value of useN,
threshold	NULL if standardize = FALSE, otherwise the 1-0.05/m quantile of the t-distribution with B-1 degrees of freedom, where m is the number of variables and B is the number of logic regression models composing object,
mu	mu (if standardize = TRUE), or NULL (otherwise),
iter	iter.

Author(s)

Holger Schwender, [e-mail]

References

Schwender, H., Ruczinski, I., Ickstadt, K. (2011). Testing SNPs and Sets of SNPs for Importance in Association Studies. Biostatistics, 12, 18-32.

See Also

logic.bagging, logicFS, vim.logicFS, vim.set, vim.ebam, vim.chisq

holgerschw/logicFS documentation built on April 15, 2020, 10:42 p.m.