fitModels: Return data.table with model fits for probabilities.

In david-salgado/categObsPredModelParam: Class and methods for the parameters of a categorical observation- prediction model

Description

fitModels computes model fits for probabilities.

Usage

fitModels(object, fitParam, na.as.category)

## S4 method for signature 'categObsPredModelParam,fitParam,logical'
fitModels(object, fitParam, na.as.category = FALSE)

Arguments

object	Object of class categObsPredModelParam.
fitParam	Object of class fitParam.
na.as.category	logical with default to FALSE to deal with NA values in the model. If TRUE the missing values are treated as a new category.

Value

Object of class categObsPredModelParam with the slot modelFits computed with the fitted models.

Examples

## Not run: 
  fitPar <- new(Class = 'fitParam',
  edData = FFall_AS.StQ, rawData = FGall_AS.StQ, 
  selParam = list(ntreeTry=1000, stepFactor=2, improve=0.05, 
                  trace=TRUE, plot=TRUE, doBest = TRUE, 
                  ptrain = 0.8, DD = DDactu),
                  valParam = list(edEffInd = effInd, priorBin = 5, 
                  dataVal = c('Train','Test')))
                  
 ObsPredPar1 <- new(Class = 'categObsPredModelParam',
                  Data = FGall_AS.StQ,
                  VarRoles = list(Units = IDUnits,
                  Domains = character(0),
                  DesignW = DesignW,
                  Regressands = Regressands,
                  Regressors = Regressors
                  ))
                  
ObsPredPar1 <-  fitModels(ObsPredPar1, fitPar, na.as.category)

## End(Not run)

david-salgado/categObsPredModelParam documentation built on Dec. 3, 2020, 1:42 p.m.