plot_taus {pqrfe}

Plot multiple penalized quantile regression

Description

plot penalized quantile regression for several taus

Usage

plot_taus(
  Beta,
  tau = 1:9/10,
  D,
  col = 2,
  lwd = 1,
  lty = 2,
  pch = 16,
  cex.axis = 1,
  cex.lab = 1,
  main = "",
  shadow = "gray90"
)

Arguments

Beta

Numeric array, with three dimmensions: 1) tau, 2) coef., lower bound, upper bound, 3) exploratory variables.

tau

Numeric vector, identifies the percentiles.

D

covariate's number.

col

color.

lwd

line width.

lty

line type.

pch

point character.

cex.axis

cex axis length.

cex.lab

cex axis length.

main

title.

shadow

color of the Confidence Interval 95%

Value

None

Examples

n = 10
m = 5
d = 4
N = n*m
L = N*d
x = matrix(rnorm(L), ncol=d, nrow=N)
subj = rep(1:n, each=m)
alpha = rnorm(n)
beta = rnorm(d)
eps = rnorm(N)
y = as.vector(x %*% beta + rep(alpha, each=m) + eps)

Beta = mpqr(x,y,subj,tau=1:9/10, effect="lasso", c = Inf)
plot_taus(Beta,tau=1:9/10,D=1)