Regression

These are the available functions for regression. See each function's help topic in the TIBCO Enterprise Runtime for R Language Reference for more information.

Function name	Title description
`.lm.fit`	General fitting for linear (regression) models
`.kappa_tri`	Compute the Exact or Estimated Condition Number
`add1.glm`	Add a Single Term to a Linear Model
`add1.lm`	Add a Single Term to a Linear Model
`anova.glm`	Analysis of Deviance for Generalized Linear Model Fits
`anova.glmlist`	Analysis of Deviance for Generalized Linear Model Fits
`cooks.distance`	Regression Deletion Diagnostics
`cooks.distance.glm`	Regression Deletion Diagnostics
`cooks.distance.lm`	Regression Deletion Diagnostics
`covratio`	Regression Deletion Diagnostics
`dfbeta`	Regression Deletion Diagnostics
`dfbeta.lm`	Regression Deletion Diagnostics
`dfbetas`	Regression Deletion Diagnostics
`dfbetas.lm`	Regression Deletion Diagnostics
`dffits`	Regression Deletion Diagnostics
`dummy.coef`	Extract Original Coefficients from a Linear Model
`dummy.coef.aovlist`	Extract Original Coefficients from a Linear Model
`dummy.coef.lm`	Extract Original Coefficients from a Linear Model
`effects`	Single Degree-of-freedom Effects from a Fitted Model
`effects.glm`	Single Degree-of-freedom Effects from a Fitted Model
`effects.lm`	Single Degree-of-freedom Effects from a Fitted Model
`glm`	Fit a Generalized Linear Model
`glm.control`	Set Control Parameters for Generalized Linear Model
`glm.fit`	Fit a GLM without Computing the Model Matrix
`glm.object`	Generalized Linear Model Object
`hat`	Hat Diagonal Regression Diagnostic
`hatvalues`	Regression Deletion Diagnostics
`hatvalues.lm`	Regression Deletion Diagnostics
`influence`	Regression Diagnostics
`influence.glm`	Regression Diagnostics
`influence.lm`	Regression Diagnostics
`influence.measures`	Regression Deletion Diagnostics
`isoreg`	Isotonic / Monotone Regression
`kappa`	Compute the Exact or Estimated Condition Number
`kappa.default`	Compute the Exact or Estimated Condition Number
`kappa.lm`	Compute the Exact or Estimated Condition Number
`kappa.qr`	Compute the Exact or Estimated Condition Number
`lm`	Fit Linear Regression Model
`lm.fit`	General fitting for linear (regression) models
`lm.influence`	Regression Diagnostics
`lm.object`	Linear Least Squares Model Object
`lm.wfit`	General fitting for linear (regression) models
`lowess`	Scatter Plot Smoothing
`lsfit`	Linear Least-Squares Fit
`mlm.object`	Linear Least Squares Model Object
`poly`	Compute Orthogonal Polynomials
`polym`	Compute Orthogonal Polynomials
`predict.nls`	Predicting from Nonlinear Least Squares Fits
`predict.poly`	Compute Orthogonal Polynomials
`print.dummy_coef`	Extract Original Coefficients from a Linear Model
`print.dummy_coef_list`	Extract Original Coefficients from a Linear Model
`print.infl`	Regression Deletion Diagnostics
`print.summary.lm`	Summary Method for Linear Models
`print.summary.mlm`	Summary Method for Linear Models
`proj`	Projection Matrix
`proj.aov`	Projection Matrix
`proj.aovlist`	Projection Matrix
`proj.default`	Projection Matrix
`proj.lm`	Projection Matrix
`rstandard`	Regression Deletion Diagnostics
`rstandard.glm`	Regression Deletion Diagnostics
`rstandard.lm`	Regression Deletion Diagnostics
`rstudent`	Regression Deletion Diagnostics
`rstudent.glm`	Regression Deletion Diagnostics
`rstudent.lm`	Regression Deletion Diagnostics
`stat.anova`	Add Statistics Columns to an Anova Table
`summary.glm`	Summary Method for Fitted Generalized Linear Models
`summary.infl`	Regression Deletion Diagnostics
`summary.lm`	Summary Method for Linear Models
`summary.mlm`	Summary Method for Linear Models