vintalyse: Vintage analysis of loan default rates
In TheProfitTable/loanportr: Loan portfolio analysis in R

Description Usage Arguments Details Value Note Examples

produces

1 2	vintalyse(data, period_dim = "loan_period", month_dim = "orig_month", segmenter_level = 1, var1, var2)

`data`	a monthly loan performance level data frame in standard data dictionary format
`period_dim`	the name of the period dimension used to do the vintage analysis. Usually either "loan_period" or "fpd_period". Note, must be input as a "string".
`month_dim`	the name of the month dimension used to do the vintage analysis. Usually either "orig_month" or "fpd_month". Note, must be input as a "string".
`segmenter_level`	1, 2 or 3. Default = 1. When 1 then no segmentation will be done when doing vintage analysis. If 2, then segmentation will be done by to the variable entered as var1. If 3, then segmentation will be done by var1 and var2. It is very important to enter the correct value here.
`var1`	the main variable to segment the vintage analysis by. Must be provided as "string" and must be a categorical variable. See Note below.
`var2`	if a second level of segmentation is required, this is the second level.

vintalyse

A data set used for plotting default vintage analysis.

Each level of the var1 and var2 pararmeters need to have sufficient volume to produce meaningful results. When creating a plot for the vintage analysis, the var1 and var2 parameters need to be either filtered upon or used to create a grid.

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default_summary <- vintalyse(df, "loan_period", "orig_month")
default_summary_var1 <- vintalyse(df, "loan_period", "orig_month", segmenter_level = 3, var1 = "fico_bin")
default_summary_var2 <- vintalyse(df, "loan_period", "orig_month", segmenter_level = 3, var1 = "fico_bin", "occpy_sts")