rid
From lrmest v3.0
by Ajith Dissanayake
Ordinary Ridge Regression Estimator
This function can be used to find the Ordinary Ridge Regression Estimated values and corresponding scalar Mean Square Error (MSE) value. Further the variation of MSE can be determined graphically.
Usage
rid(formula, k, data = NULL, na.action, ...)
Arguments
- formula
- in this section interested model should be given. This should be given as a
formula
. - k
- a single numeric value or a vector of set of numeric values. See
Examples . - data
- an optional data frame, list or environment containing the variables in the model. If not found in
data
, the variables are taken fromenvironment(formula)
, typically the environment from which the function is called. - na.action
- if the dataset contain
NA
values, thenna.action
indicate what should happen to thoseNA
values. - ...
- currently disregarded.
Details
Since formula has an implied intercept term, use either y ~ x - 1
or y ~ 0 + x
to remove the intercept.
Use plot
so as to obtain the variation of scalar MSE values graphically. See
Value
- If
k
is a single numeric values thenrid
returns the Ordinary Ridge Regression Estimated values, standard error values, t statistic values, p value and corresponding scalar MSE value. Ifk
is a vector of set of numeric values thenrid
returns all the scalar MSE values and corresponding parameter values of Ordinary Ridge Regression Estimator.
References
Hoerl, A.E. and Kennard, R.W. (1970) Ridge Regression Biased estimation for non orthogonal problem, 12, pp.55--67.
See Also
Examples
## Portland cement data set is used.
data(pcd)
k<-0.01
rid(Y~X1+X2+X3+X4-1,k,data=pcd) # Model without the intercept is considered.
## To obtain the variation of MSE of Ordinary Ridge Regression Estimator.
data(pcd)
k<-c(0:10/10)
plot(rid(Y~X1+X2+X3+X4-1,k,data=pcd),
main=c("Plot of MSE of Ordinary Ridge Regression Estimator"),
type="b",cex.lab=0.6,adj=1,cex.axis=0.6,cex.main=1,las=1,lty=3,cex=0.6)
mseval<-data.frame(rid(Y~X1+X2+X3+X4-1,k,data=pcd))
smse<-mseval[order(mseval[,2]),]
points(smse[1,],pch=16,cex=0.6)
Community examples
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