plot.biasliu {liureg} | R Documentation |
Trade-off between bias, variance and MSE of the Liu regression against vector or scalar value of biasing parameter d
.
## S3 method for class 'biasliu'
plot(x, abline = TRUE, ...)
x |
An object of "liu". |
abline |
Horizontal and vertical lines show the minimum value of the Liu MSE at certain value of biasing parameter |
... |
No presently used in this implementation. |
The effect of multicollinearity on the coefficients can be identified using different graphical display. One of them is plot of bias, variance and MSE. Addition of biasing parameter d
lead to a substantial impact on variance and MSE of Liu regression estimates. Therefore, a trade-off is made between bias and variance to have an acceptable MSE. The plot.biasliu
can be helpful for selection of optimal value of biasing parameter d
.
Nothing returned
Muhammad Imdad Ullah, Muhammad Aslam
Imdad, M. U. (2017). Addressing Linear Regression Models with Correlated Regressors: Some Package Development in R (Doctoral Thesis, Department of Statistics, Bahauddin Zakariya University, Multan, Pakistan).
Imdadullah, M., Aslam, M., and Altaf, S. (2017). liureg: A comprehensive R Package for the Liu Estimation of Linear Regression Model with Collinear Regressors. The R Journal, 9 (2), 232–247.
Kalivas, J. H., and Palmer, J. (2014). Characterizing multivariate calibration tradeoff (bias, variance, selectivity, and sensitivity) to select model tuning parameters. Journal of Chemometrics, 28(5), 347–357. https://doi.org/10.1002/cem.2555.
Liu model fitting liu
, Liu residuals residuals.liu
, Liu PRESS press.liu
, Testing of Liu Coefficients summary.liu
mod<-liu(y~., as.data.frame(Hald), d = seq(-5, 5, 0.1))
## for indication of vertical line (biasing parameter d) and
## horizontal line (minimum Liu MSE value corresponding to vertical line)
plot.biasliu(mod)
## without horizontal and vertical line
plot.biasliu(mod, abline = FALSE)