regD: Regression of Conventional Way with Rich Diagnostics

In sasLM: 'SAS' Linear Model

Regression of Conventional Way with Rich Diagnostics

Description

regD provides rich diagnostics such as student residual, leverage(hat), Cook's D, studentized deleted residual, DFFITS, and DFBETAS.

Usage

regD(Formula, Data)

Arguments

Formula	a conventional formula for a linear model
Data	a data.frame to be analyzed

Details

It performs the conventional regression analysis. This does not use g2 inverse, therefore it cannot handle a singular matrix. If the model(design) matrix is not full rank, use REG or fewer parameters.

Value

Coefficients	conventional coefficients summary with Wald statistics
Diagnostics	Diagnostics table for detecting outlier or influential/leverage points. This includes fitted (Predicted), residual (Residual), standard error of residual(se_resid), studentized residual(RStudent), hat(Leverage), Cook's D, studentized deleted residual(sdResid), DIFFITS, and COVRATIO.
DFBETAS	Column names are the names of coefficients. Each row shows how much each coefficient is affected by deleting the corressponding row of observation.

Author(s)

Kyun-Seop Bae [e-mail]

Examples

  regD(uptake ~ conc, CO2)

sasLM documentation built on Nov. 19, 2023, 5:12 p.m.