Create Logistic
model object for lifetime probability of
default
Create and analyze a Logistic
model object to calculate
the lifetime probability (PD) of default using this workflow:
Use fitLifetimePDModel
to create a
Logistic
model object.
Use predict
to predict the conditional PD and predictLifetime
to predict the lifetime PD.
Use modelDiscrimination
to return AUROC and ROC data.
Use modelAccuracy
to return the RMSE of the observed and
predicted PD data.
creates a LogisticPDModel
= fitLifetimePDModel(data
,ModelType
)Logistic
PD model object and sets the
data
and ModelType
properties.
If you do not specify variable information for
IDVar
, AgeVar
,
LoanVars
, MacroVars
, and
ResponseVar
, then:
IDVar
is set to the first column in
the data
input.
LoanVars
is set to include all
columns from the second to the second-to-last columns of the
data
input.
ResponseVar
is set to the last column
in the data
input.
specifies options using one or more name-value pair arguments in
addition to the input arguments in the previous syntax. The optional
name-value pair arguments set model object properties. For
example, LogisticPDModel
= fitLifetimePDModel(___,Name,Value
)LogisticPDModel =
fitLifetimePDModel(data(TrainDataInd,:),"Logistic",'ModelID',"Logistic_A",'Description',"Logisitic_model",'AgeVar',"YOB",'IDVar',"ID",'LoanVars',"ScoreGroup','MacroVars',{'GDP','Market',}'ResponseVar',"Default")
creates a Logistic
model object.
predict | Compute conditional PD |
predictLifetime | Compute cumulative lifetime PD, marginal PD, and survival probability |
modelDiscrimination | Compute AUROC and ROC data |
modelAccuracy | Compute RMSE of predicted and observed PDs on grouped data |
[1] Baesens, Bart, Daniel Roesch, and Harald Scheule. Credit Risk Analytics: Measurement Techniques, Applications, and Examples in SAS. Wiley, 2016.
[2] Bellini, Tiziano. IFRS 9 and CECL Credit Risk Modelling and Validation: A Practical Guide with Examples Worked in R and SAS. San Diego, CA: Elsevier, 2019.
[3] Breeden, Joseph. Living with CECL: The Modeling Dictionary. Santa Fe, NM: Prescient Models LLC, 2018.