Implements QICD algorithm
QICD(
y,
x,
tau = 0.5,
lambda,
intercept = TRUE,
penalty = "SCAD",
initial_beta = NULL,
maxin = 100,
maxout = 20,
eps = 1e-05,
coef.cutoff = 1e-08,
a = 3.7,
scalex = TRUE,
...
)
response variable, length n vector
input nxp matrix, of dimension nobs x nvars; each row is an observation vector.
the quantile value
the tuning parameter (numeric value > 0)
a logical value,should intercept be fitted (default=TRUE) (intercept should be included when using splines)
The name of the penalty function ("SCAD", "MCP", "LASSO")
Vector containing initial values for intercept (if included) and x coefficients. Should be in the form (intercept, coefficients) intercept should be left out if intercept=FALSE.
maximum number of iterations for inside coordinate descent,default value is 100
maximum number of iterations for outside MM step, default value is 20
The convergence threshold for coordinate descent and majorization minimization step
Threshold for determining nonzero coefficients
Scale parameter, the default value is 3.7 (>2 for SCAD, >1 for MCP, not used in LASSO)
Whether predictors are centered and scaled
additional parameters