Package index • ModTools

All functions

BestCut(): Best Cutpoint for a ROC Curve

BreuschPaganTest(): Breusch-Pagan Test

CP() print(<CP>) plot(<CP>): Complexity Parameter of an rpart Model

CoeffDiffCI(): Confidence Interval for the Difference of Two Coefficients in a Linear Model

FitMod() predict(<FitMod>) plot(<FitMod>) summary(<FitMod>) drop1(<FitMod>): Wrapper for Several Model Functions

LeafRates() plot(<LeafRates>): Leafrates for the Nodes of an 'rpart' Tree

LogitBoost(): LogitBoost Classification Algorithm

ModTools-package ModTools: Regression and Classification Tools

Node(): Nodes and Splits in an rpart Tree

OverSample() UnderSample(): Oversample and Undersample

PlotLift(): Lift Charts to Compare Binary Predictive Models

PredictCI(): Confidence Intervals for Predictions of a GLM

ROC(): Build a ROC curve

RefLevel(): Used Reference Levels in a Linear Model

Response(): Extract the Response from Several Models

RobSummary(): Robust Summary for Linear Models

Rules(): Extract Rules from 'rpart' Object

SplitTrainTest(): Split DataFrame in Train an Test Sample

TModC() plot(<TModC>): Compare Classification Models

Tune(): Tune Classificators

VarImp() plot(<VarImp>) print(<VarImp>): Variable Importance for Regression and Classification Models

bioChemists: article production by graduate students in biochemistry Ph.D. programs

d.glass: Measurements of Forensic Glass Fragments

d.pima d.pima2: Diabetes survey on Pima Indians

predict(<zeroinfl>) residuals(<zeroinfl>) coef(<zeroinfl>) vcov(<zeroinfl>) terms(<zeroinfl>) model.matrix(<zeroinfl>): Methods for zeroinfl Objects

Tobit(): Tobit Regression

zeroinfl(): Zero-inflated Count Data Regression

zeroinfl.control(): Control Parameters for Zero-inflated Count Data Regression