get_psi_all: Calculate Population Stability Index (PSI) `get_psi` is used to calculate Population Stability Index (PSI) of an independent variable. `get_psi_all` can loop through PSI for all specified independent variables.

Description

Calculate Population Stability Index (PSI) get_psi is used to calculate Population Stability Index (PSI) of an independent variable. get_psi_all can loop through PSI for all specified independent variables.

Usage

get_psi_all(dat, x_list = NULL, target = NULL, dat_test = NULL,
  breaks_list = NULL, occur_time = NULL, start_date = NULL,
  cut_date = NULL, oot_pct = 0.7, pos_flag = NULL,
  parallel = FALSE, ex_cols = NULL, as_table = FALSE, g = 10,
  bins_no = TRUE, note = FALSE)
get_psi(dat, x, target = NULL, dat_test = NULL, occur_time = NULL,
  start_date = NULL, cut_date = NULL, pos_flag = NULL,
  breaks = NULL, breaks_list = NULL, oot_pct = 0.7, g = 10,
  as_table = TRUE, note = FALSE, bins_no = TRUE)

Arguments

dat

A data.frame with independent variables and target variable.

x_list

Names of independent variables.

target

The name of target variable.

dat_test

A data.frame of test data. Default is NULL.

breaks_list

A table containing a list of splitting points for each independent variable. Default is NULL.

occur_time

The name of the variable that represents the time at which each observation takes place.

start_date

The earliest occurrence time of observations.

cut_date

Time points for spliting data sets, e.g. : spliting Actual and Expected data sets.

oot_pct

Percentage of observations retained for overtime test (especially to calculate PSI). Defualt is 0.7

pos_flag

Value of positive class, Default is "1".

parallel

Logical, parallel computing. Default is FALSE.

ex_cols

Names of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.

as_table

Logical, output results in a table. Default is TRUE.

Number of initial breakpoints for equal frequency binning.

bins_no

Logical, add serial numbers to bins. Default is TRUE.

note

Logical, outputs info. Default is TRUE.

The name of an independent variable.

breaks

Splitting points for an independent variable. Default is NULL.

Details

PSI Rules for evaluating the stability of a predictor Less than 0.02: Very stable 0.02 to 0.1: Stable 0.1 to 0.2: Unstable 0.2 to 0.5] : Change more than 0.5: Great change

Examples

Run this code

# NOT RUN {
#  dat_test is null
get_psi(dat = UCICreditCard, x = "PAY_3", occur_time = "apply_date")
# dat_test is not all
# train_test split
train_test = train_test_split(dat = UCICreditCard, prop = 0.7, split_type = "OOT",
                             occur_time = "apply_date", start_date = NULL, cut_date = NULL,
                            save_data = FALSE, note = FALSE)
dat_ex = train_test$train
dat_ac = train_test$test
# generate psi table
get_psi(dat = dat_ex, dat_test = dat_ac, x = "PAY_3",
       occur_time = "apply_date", bins_no = TRUE)
# }

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