qr {alqrfe} | R Documentation |
quantile regression
Description
Estimate quantile regression with fixed effects for one tau
Usage
qr(x, y, subj, tau = 0.5, method = "qr", ngrid = 20, inf = 1e-08, digt = 4)
Arguments
x |
Numeric matrix, covariates |
y |
Numeric vector, outcome. |
subj |
Numeric vector, identifies the unit to which the observation belongs. |
tau |
Numeric, identifies the percentile. |
method |
Factor, "qr" quantile regression, "qrfe" quantile regression with fixed effects, "lqrfe" Lasso quantile regression with fixed effects, "alqr" adaptive Lasso quantile regression with fixed effects. |
ngrid |
Numeric scalar greater than one, number of BIC to test. |
inf |
Numeric scalar, internal value, small value. |
digt |
Numeric scalar, internal value greater than one, define "zero" coefficient. |
Value
alpha Numeric vector, intercepts' coefficients.
beta Numeric vector, exploratory variables' coefficients.
lambda Numeric, estimated lambda.
res Numeric vector, percentile residuals.
tau Numeric scalar, the percentile.
penalty Numeric scalar, indicate the chosen effect.
sig2_alpha Numeric vector, intercepts' standard errors.
sig2_beta Numeric vector, exploratory variables' standard errors.
Tab_alpha Data.frame, intercepts' summary.
Tab_beta Data.frame, exploratory variables' summary.
Mat_alpha Numeric matrix, intercepts' summary.
Mat_beta Numeric matrix, exploratory variables' summary.
method Factor, method applied.
References
Koenker, R. (2004) "Quantile regression for longitudinal data", J. Multivar. Anal., 91(1): 74-89, <doi:10.1016/j.jmva.2004.05.006>
Examples
# Example 1
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 = x %*% beta + matrix(rep(alpha, each=m) + eps)
y = as.vector(y)
m1 = qr(x,y,subj,tau=0.75, method="qrfe")
m1
m2 = qr(x,y,subj,tau=0.3, method="lqrfe", ngrid = 10)
m2
# Example 2, from MASS package
Rabbit = MASS::Rabbit
Rabbit$Treatment = ifelse(Rabbit$Treatment=="Control",0,1)
Rabbit$Animal = ifelse(Rabbit$Animal == "R1",1,ifelse(Rabbit$Animal == "R2",2,
ifelse(Rabbit$Animal == "R3",3,ifelse(Rabbit$Animal == "R4",4,5))))
X = matrix(cbind(Rabbit$Dose,Rabbit$Treatment), ncol=2)
m3 = qr(x=X, y=Rabbit$BPchange, subj=Rabbit$Animal,tau=0.5, method="alqrfe", ngrid = 10)
m3