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Performs monotonic binning of numeric risk factor in credit rating models (PD, LGD, EAD) development. All functions handle both binary and continuous target variable. Functions that use isotonic regression in the first stage of binning process have an additional feature for correction of minimum percentage of observations and minimum target rate per bin. Additionally, monotonic trend can be identified based on raw data or, if known in advance, forced by functions' argument. Missing values and other possible special values are treated separately from so-called complete cases.

copied from cf-post-staging / r-monobin
Type Size Name Uploaded Downloads Labels
conda 139.1 kB | noarch/r-monobin-0.2.4-r44hc72bb7e_1.conda  6 months and 22 days ago 375 main
conda 139.6 kB | noarch/r-monobin-0.2.4-r45hc72bb7e_1.conda  6 months and 22 days ago 399 main
conda 137.5 kB | noarch/r-monobin-0.2.4-r43hc72bb7e_0.conda  1 year and 1 month ago 743 main
conda 139.2 kB | noarch/r-monobin-0.2.4-r44hc72bb7e_0.conda  1 year and 1 month ago 752 main

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