mqr_alpha {alqrfe} | R Documentation |
Estimate QR intercepts for several taus
mqr_alpha(
x,
y,
subj,
tau = 1:9/10,
method = "qr",
ngrid = 20,
inf = 1e-08,
digt = 4
)
x |
Numeric matrix, covariates |
y |
Numeric vector, outcome. |
subj |
Numeric vector, identifies the unit to which the observation belongs. |
tau |
Numeric vector, identifies the percentiles. |
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. |
Alpha Numeric array, with three dimmensions: 1) tau, 2) coef., lower bound, upper bound, 3) exploratory variables.
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)
Alpha = mqr(x,y,subj,tau=1:9/10, method="qr", ngrid = 10)
Alpha