# plot.KERE: Plot coefficients from a "KERE" object In KERE: Expectile Regression in Reproducing Kernel Hilbert Space

## Description

Produces a coefficient profile plot of the coefficient paths for a fitted `KERE` object.

## Usage

 ```1 2``` ```## S3 method for class 'KERE' plot(x, ...) ```

## Arguments

 `x` fitted `KERE` model. `...` other graphical parameters to plot.

## Details

A coefficient profile plot is produced. The x-axis is log(λ). The y-axis is the value of fitted α's.

## Author(s)

Yi Yang, Teng Zhang and Hui Zou
Maintainer: Yi Yang <[email protected]>

## References

Y. Yang, T. Zhang, and H. Zou. "Flexible Expectile Regression in Reproducing Kernel Hilbert Space." ArXiv e-prints: stat.ME/1508.05987, August 2015.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```# create data N <- 200 X1 <- runif(N) X2 <- 2*runif(N) X3 <- 3*runif(N) SNR <- 10 # signal-to-noise ratio Y <- X1**1.5 + 2 * (X2**.5) + X1*X3 sigma <- sqrt(var(Y)/SNR) Y <- Y + X2*rnorm(N,0,sigma) X <- cbind(X1,X2,X3) # set gaussian kernel kern <- rbfdot(sigma=0.1) # define lambda sequence lambda <- exp(seq(log(0.5),log(0.01),len=10)) # run KERE m1 <- KERE(x=X, y=Y, kern=kern, lambda = lambda, omega = 0.5) # plot the solution paths plot(m1) ```

KERE documentation built on May 29, 2017, 10:49 a.m.