Results of the Each Data and Data Splits

Results of the Each Data and Data Splits

Usage

Estimate_Models(DataSet, yvar, exog = NULL, xvec, xadd, type, dnames)

Arguments

DataSet

The name of the Dataset.

yvar

Y variable.

exog

is a vector to be subtract from the calculation.

xvec

is a vector of the variables to be used.

xadd

is an additional vector to be used.

type

can be RF, GLM, MLM, BAG, and GBM.

dnames

is the unique values of exog.

Value

The output from Estimate_Models.

Examples

# \donttest{
sample_data <- sample_data[c(1:750),]
m2.xvar0 <- c("sex","married","age","havejob","educ","rural","region","income")
CCP.RF <- Estimate_Models(sample_data, yvar = c("Loan.Type"),
exog = "political.afl", xvec = m2.xvar0,
xadd = "networth", type = "RF", dnames = c("0","1"))
#> + Fold01: mtry=2 
#> - Fold01: mtry=2 
#> + Fold01: mtry=5 
#> - Fold01: mtry=5 
#> + Fold01: mtry=9 
#> - Fold01: mtry=9 
#> + Fold02: mtry=2 
#> - Fold02: mtry=2 
#> + Fold02: mtry=5 
#> - Fold02: mtry=5 
#> + Fold02: mtry=9 
#> - Fold02: mtry=9 
#> + Fold03: mtry=2 
#> - Fold03: mtry=2 
#> + Fold03: mtry=5 
#> - Fold03: mtry=5 
#> + Fold03: mtry=9 
#> - Fold03: mtry=9 
#> + Fold04: mtry=2 
#> - Fold04: mtry=2 
#> + Fold04: mtry=5 
#> - Fold04: mtry=5 
#> + Fold04: mtry=9 
#> - Fold04: mtry=9 
#> + Fold05: mtry=2 
#> - Fold05: mtry=2 
#> + Fold05: mtry=5 
#> - Fold05: mtry=5 
#> + Fold05: mtry=9 
#> - Fold05: mtry=9 
#> + Fold06: mtry=2 
#> - Fold06: mtry=2 
#> + Fold06: mtry=5 
#> - Fold06: mtry=5 
#> + Fold06: mtry=9 
#> - Fold06: mtry=9 
#> + Fold07: mtry=2 
#> - Fold07: mtry=2 
#> + Fold07: mtry=5 
#> - Fold07: mtry=5 
#> + Fold07: mtry=9 
#> - Fold07: mtry=9 
#> + Fold08: mtry=2 
#> - Fold08: mtry=2 
#> + Fold08: mtry=5 
#> - Fold08: mtry=5 
#> + Fold08: mtry=9 
#> - Fold08: mtry=9 
#> + Fold09: mtry=2 
#> - Fold09: mtry=2 
#> + Fold09: mtry=5 
#> - Fold09: mtry=5 
#> + Fold09: mtry=9 
#> - Fold09: mtry=9 
#> + Fold10: mtry=2 
#> - Fold10: mtry=2 
#> + Fold10: mtry=5 
#> - Fold10: mtry=5 
#> + Fold10: mtry=9 
#> - Fold10: mtry=9 
#> Aggregating results
#> Selecting tuning parameters
#> Fitting mtry = 2 on full training set
#> + Fold01: mtry=2 
#> - Fold01: mtry=2 
#> + Fold01: mtry=5 
#> - Fold01: mtry=5 
#> + Fold01: mtry=9 
#> - Fold01: mtry=9 
#> + Fold02: mtry=2 
#> - Fold02: mtry=2 
#> + Fold02: mtry=5 
#> - Fold02: mtry=5 
#> + Fold02: mtry=9 
#> - Fold02: mtry=9 
#> + Fold03: mtry=2 
#> - Fold03: mtry=2 
#> + Fold03: mtry=5 
#> - Fold03: mtry=5 
#> + Fold03: mtry=9 
#> - Fold03: mtry=9 
#> + Fold04: mtry=2 
#> - Fold04: mtry=2 
#> + Fold04: mtry=5 
#> - Fold04: mtry=5 
#> + Fold04: mtry=9 
#> - Fold04: mtry=9 
#> + Fold05: mtry=2 
#> - Fold05: mtry=2 
#> + Fold05: mtry=5 
#> - Fold05: mtry=5 
#> + Fold05: mtry=9 
#> - Fold05: mtry=9 
#> + Fold06: mtry=2 
#> - Fold06: mtry=2 
#> + Fold06: mtry=5 
#> - Fold06: mtry=5 
#> + Fold06: mtry=9 
#> - Fold06: mtry=9 
#> + Fold07: mtry=2 
#> - Fold07: mtry=2 
#> + Fold07: mtry=5 
#> - Fold07: mtry=5 
#> + Fold07: mtry=9 
#> - Fold07: mtry=9 
#> + Fold08: mtry=2 
#> - Fold08: mtry=2 
#> + Fold08: mtry=5 
#> - Fold08: mtry=5 
#> + Fold08: mtry=9 
#> - Fold08: mtry=9 
#> + Fold09: mtry=2 
#> - Fold09: mtry=2 
#> + Fold09: mtry=5 
#> - Fold09: mtry=5 
#> + Fold09: mtry=9 
#> - Fold09: mtry=9 
#> + Fold10: mtry=2 
#> - Fold10: mtry=2 
#> + Fold10: mtry=5 
#> - Fold10: mtry=5 
#> + Fold10: mtry=9 
#> - Fold10: mtry=9 
#> Aggregating results
#> Selecting tuning parameters
#> Fitting mtry = 2 on full training set
#> + Fold01: mtry=2 
#> - Fold01: mtry=2 
#> + Fold01: mtry=5 
#> - Fold01: mtry=5 
#> + Fold01: mtry=9 
#> - Fold01: mtry=9 
#> + Fold02: mtry=2 
#> - Fold02: mtry=2 
#> + Fold02: mtry=5 
#> - Fold02: mtry=5 
#> + Fold02: mtry=9 
#> - Fold02: mtry=9 
#> + Fold03: mtry=2 
#> - Fold03: mtry=2 
#> + Fold03: mtry=5 
#> - Fold03: mtry=5 
#> + Fold03: mtry=9 
#> - Fold03: mtry=9 
#> + Fold04: mtry=2 
#> - Fold04: mtry=2 
#> + Fold04: mtry=5 
#> - Fold04: mtry=5 
#> + Fold04: mtry=9 
#> - Fold04: mtry=9 
#> + Fold05: mtry=2 
#> - Fold05: mtry=2 
#> + Fold05: mtry=5 
#> - Fold05: mtry=5 
#> + Fold05: mtry=9 
#> - Fold05: mtry=9 
#> + Fold06: mtry=2 
#> - Fold06: mtry=2 
#> + Fold06: mtry=5 
#> - Fold06: mtry=5 
#> + Fold06: mtry=9 
#> - Fold06: mtry=9 
#> + Fold07: mtry=2 
#> - Fold07: mtry=2 
#> + Fold07: mtry=5 
#> - Fold07: mtry=5 
#> + Fold07: mtry=9 
#> - Fold07: mtry=9 
#> + Fold08: mtry=2 
#> - Fold08: mtry=2 
#> + Fold08: mtry=5 
#> - Fold08: mtry=5 
#> + Fold08: mtry=9 
#> - Fold08: mtry=9 
#> + Fold09: mtry=2 
#> - Fold09: mtry=2 
#> + Fold09: mtry=5 
#> - Fold09: mtry=5 
#> + Fold09: mtry=9 
#> - Fold09: mtry=9 
#> + Fold10: mtry=2 
#> - Fold10: mtry=2 
#> + Fold10: mtry=5 
#> - Fold10: mtry=5 
#> + Fold10: mtry=9 
#> - Fold10: mtry=9 
#> Aggregating results
#> Selecting tuning parameters
#> Fitting mtry = 2 on full training set
# }