select.pqrBayes: Variable selection for a pqrBayes object

In pqrBayes: Bayesian Penalized Quantile Regression

Variable selection for a pqrBayes object

Description

Variable selection for a pqrBayes object

Usage

pqrBayes.select(object,sparse=T,model="linear")

Arguments

object	a pqrBayes object.
sparse	logical flag. If TRUE, the sparse model is used for variable selection. The default value is TRUE.
model	the model to be fitted. Users can also choose "linear" for a linear model, "VC" for a varying coefficient model or "group for group LASSO.

Details

For class ‘Sparse’, the median probability model (MPM) (Barbieri and Berger, 2004) is used to identify predictors that are significantly associated with the response variable. For class ‘NonSparse’, variable selection is based on 95% credible interval. Please check the references for more details about the variable selection.

Value

an object of class ‘select’ is returned, which includes the indices of the selected predictors (e.g. genetic factors).

References

Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y. and Wu, C. (2023). Robust Bayesian variable selection for gene-environment interactions. Biometrics, 79(2), 684-694 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/biom.13670")}

Barbieri, M.M. and Berger, J.O. (2004). Optimal predictive model selection. Ann. Statist, 32(3):870–897

See Also

pqrBayes

Examples

## The quantile regression model
data(data)
data = data$data_linear
g=data$g
y=data$y
e=data$e

fit1=pqrBayes(g,y,u=NULL,e,d = NULL,quant=0.5,spline=NULL,model="linear")
sparse=TRUE
select=pqrBayes.select(obj = fit1,sparse = sparse,model="linear")

## The quantile varying coefficient model
data(data)
data = data$data_varying
g=data$g
y=data$y
u=data$u
e=data$e
spline = list(kn=2,degree=2)
fit1=pqrBayes(g,y,u,e,d = NULL,quant=0.5,spline = spline,model="VC")
sparse=TRUE
select=pqrBayes.select(obj = fit1,sparse = sparse,model="VC")
select


## Non-sparse example with VC model
sparse <- FALSE
spline <- list(kn = 2, degree = 2)

fit2 <- pqrBayes(
  g = g, y = y, u = u, e = e, d = NULL,
  quant = 0.5,
  spline = spline,
  sparse = sparse,
  model = "VC"
)

select <- pqrBayes.select(obj = fit2, sparse = FALSE, model = "VC")
select

pqrBayes documentation built on June 8, 2025, 12:35 p.m.