rplots.plot {lmridge} | R Documentation |
Miscellaneous Ridge Plots
Description
Panel of three ridge related plots, df trace vs K
, RSS vs K
and PRESS vs K
for graphical judgement of optimal value of K
.
Usage
rplots.plot(x, abline = TRUE, ...)
Arguments
x |
An object of class "lmridge" |
abline |
Vertical line to show minimum value of ridge PRESS at cartain value of biasing parameter |
... |
Not presently used in this implementation. |
Details
Function rplots.plot
can be used to plot the values of df vs K
, RSS vs K
and PRESS vs K
for scalar or vector values of biasing parameter K
. If no argument is used then a vertical line will be drawn on ridge PRESS plot to show the minimum value of PRESS at certain K
. The panel of these three plots can be helful in selecting the optimal value of biasing parameter K
.
Value
nothing
Author(s)
Muhammad Imdad Ullah, Muhammad Aslam
References
Allen, D. M. (1971). Mean Square Error of Prediction as a Criterion for Selecting Variables. Technometrics, 13, 469-475. doi:10.1080/00401706.1971.10488811.
Allen, D. M. (1974). The Relationship between Variable Selection and Data Augmentation and Method for Prediction. Technometrics, 16, 125-127. doi:10.1080/00401706.1974.10489157.
Berk, R. (2008). Statistical Learning from a Regression Perspective. Springer.
Hoerl, A. E., Kennard, R. W., and Baldwin, K. F. (1975). Ridge Regression: Some Simulation. Communication in Statistics, 4, 105-123. doi:10.1080/03610927508827232.
Hoerl, A. E. and Kennard, R. W., (1970). Ridge Regression: Biased Estimation of Nonorthogonal Problems. Technometrics, 12, 55-67. doi:10.1080/00401706.1970.10488634.
Imdad, M. U. Addressing Linear Regression Models with Correlated Regressors: Some Package Development in R (Doctoral Thesis, Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan), 2017.
See Also
The ridge model fitting lmridge
, ridge CV and GCV plots cv.plot
, variance bias trade-off plot bias.plot
, m-scale and isrm plots isrm.plot
, ridge AIC and BIC plots info.plot
, ridge and VIF trace plot.lmridge
Examples
mod <- lmridge(y~., as.data.frame(Hald), K = seq(0, 0.2, 0.005))
rplots.plot(mod)
rplots.plot(mod, abline = FALSE)