Compute RMSE of predicted and observed PDs on grouped data
[
computes the root mean squared error (RMSE) of the observed compared to the
predicted probabilities of default (PD). AccMeasure
,AccData
] = modelAccuracy(pdModel
,data
,GroupBy
)GroupBy
is
required and can be any column in the data
input (not
necessarily a model variable). The model Accuracy
function
computes the observed PD as the default rate of each group and the predicted PD
as the average PD for each group. modelAccuracy
supports
comparison against a reference model.
specifies options using one or more name-value pair arguments in addition to the
input arguments in the previous syntax.AccMeasure
,AccData
= modelAccuracy(___,Name,Value
)
[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.
fitLifetimePDModel
| Logistic
| modelDiscrimination
| predict
| predictLifetime
| Probit