slm.methods: Methods for slm objects

Description

Summarize, print, and extract objects from slm objects.

Usage

summary.slm(object, correlation, ...)
summary.mslm(object, ...)
print.slm(x, digits, ...)
print.summary.slm(x, digits, symbolic.cor, signif.stars, ...)
fitted.slm(object, ...)
residuals.slm(object, ...)
coef.slm(object, ...)

Arguments

object,x

object of class slm.

digits

minimum number of significant digits to be used for most numbers.

symbolic.cor

logical; if TRUE, the correlation of coefficients will be printed. The default is FALSE

signif.stars

logical; if TRUE, P-values are additionally encoded visually as ``significance stars'' in order to help scanning of long coefficient tables. It defaults to the `show.signif.stars' slot of `options'.

correlation

logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.

...

additional arguments passed to methods.

Value

print.slm and print.summary.slm return invisibly. fitted.slm, residuals.slm, and coef.slm return the corresponding components of the slm object.

References

Koenker, R and Ng, P. (2002). SparseM: A Sparse Matrix Package for R, http://www.econ.uiuc.edu/~roger/research

Examples

Run this code

data(lsq)
X <- model.matrix(lsq) #extract the design matrix
y <- model.response(lsq) # extract the rhs
X1 <- as.matrix(X)
slm.time <- unix.time(slm(y~X1-1) -> slm.o) # pretty fast
cat("slm time =",slm.time,"")
cat("slm Results: Reported Coefficients Truncated to 5  ","")
sum.slm <- summary(slm.o)
sum.slm$coef <- sum.slm$coef[1:5,]
sum.slm
fitted(slm.o)[1:10]
residuals(slm.o)[1:10]
coef(slm.o)[1:10]