REG: Regression of Linear Least Square, similar to SAS PROC REG

In sasLM: 'SAS' Linear Model

Regression of Linear Least Square, similar to SAS PROC REG

Description

REG is similar to SAS PROC REG.

Usage

  REG(Formula, Data, conf.level=0.95, HC=FALSE, Resid=FALSE, Weights=1,
      summarize=TRUE)

Arguments

Formula	a conventional formula for a linear model
Data	a data.frame to be analyzed
conf.level	confidence level for the confidence limit
HC	heteroscedasticity-related output is required, such as HC0, HC3, and White's first and second moment specification test
Resid	if TRUE, fitted values (y hat) and residuals will be returned
Weights	weights for each observation, usually the inverse of each variance. This should be a scalar or a vector of the same length as the number of rows of Data. Observations with nonpositive weights are excluded from the analysis, as SAS does.
summarize	If this is FALSE, REG returns just the lfit result.

Details

It performs the core function of SAS PROC REG.

Value

The result is comparable to that of SAS PROC REG.

The first part is the ANOVA table.

The second part is measures of fitness.

The third part is the estimates of coefficients.

Estimate	point estimate of parameters, coefficients
Estimable	estimability: 1=TRUE, 0=FALSE. This appears only when at least one inestimability occurs.
Std. Error	standard error of the point estimate
Lower CL	lower confidence limit with conf.level
Upper CL	upper confidence limit with conf.level
Df	degrees of freedom
t value	value for the t distribution
Pr(>|t|)	probability of a larger absolute t value from the t distribution with the residual's degrees of freedom

The above result is repeated using HC0 and HC3, followed by White's first and second moment specification test, if the HC option is specified. The t values and their p values with HC1 and HC2 are between those of HC0 and HC3.

Fitted	Fitted value or y hat in the original scale as SAS OUTPUT P= does, even with Weights. This is returned only with the Resid=TRUE option.
Residual	Residuals in the original scale as SAS OUTPUT R= does, even with Weights. This is returned only with the Resid=TRUE option.

If summarize=FALSE, REG returns;

coefficients	beta coefficients
g2	g2 inverse
rank	rank of the model matrix
DFr	degrees of freedom for the residual
SSE	sum of squared errors

Author(s)

Kyun-Seop Bae [e-mail]

See Also

lr

Examples

  REG(uptake ~ Plant + Type + Treatment + conc, CO2)
  REG(uptake ~ conc, CO2, HC=TRUE)
  REG(uptake ~ conc, CO2, Resid=TRUE)
  REG(uptake ~ conc, CO2, HC=TRUE, Resid=TRUE)
  REG(uptake ~ conc, CO2, summarize=FALSE)

sasLM documentation built on June 15, 2026, 9:07 a.m.