pro.sgpv: 'pro.sgpv' function
In zuoyi93/ProSGPV: Penalized Regression with Second-Generation P-Values

Description Usage Arguments Value See Also Examples

This function outputs the variable selection results from either one-stage algorithm or two-stage algorithm.

pro.sgpv(
  x,
  y,
  stage = c(1, 2),
  family = c("gaussian", "binomial", "poisson", "cox"),
  gvif = F
)

`x`	Independent variables, can be a `matrix` or a `data.frame`
`y`	Dependent variable, can be a `vector` or a column from a `data.frame`
`stage`	Algorithm indicator. 1 denotes the one-stage algorithm and 2 denotes the two-stage algorithm. Default is 2. When `n` is less than `p`, only the two-stage algorithm is available.
`family`	A description of the error distribution and link function to be used in the model. It can take the value of `\code{gaussian}`, `\code{binomial}`, `\code{poisson}`, and `\code{cox}`. Default is `\code{gaussian}`
`gvif`	A logical operator indicating whether a generalized variance inflation factor-adjusted null bound is used. Default is FALSE. See Fox (1992) doi: 10.1080/01621459.1992.10475190 for more details on how to calculate GVIF

A list of following components:

var.index: A vector of indices of selected variables
var.label: A vector of labels of selected variables
lambda: lambda selected by generalized information criterion in the two-stage algorithm. NULL for the one-stage algorithm
x: Input data x
y: Input data y
family: family from the input
stage: stage from the input
null.bound: Null bound in the SGPV screening
pe.can: Point estimates in the candidate set
lb.can: Lower bounds of CI in the candidate set
ub.can: Upper bounds of CI in the candidate set

print.sgpv() prints the variable selection results
coef.sgpv() extracts coefficient estimates
summary.sgpv() summarizes the OLS outputs
predict.sgpv() predicts the outcome
plot.sgpv() plots variable selection results

# prepare the data
x <- t.housing[, -ncol(t.housing)]
y <- t.housing$V9

# run ProSGPV in linear regression
out.sgpv <- pro.sgpv(x = x, y = y)

# More examples at https://github.com/zuoyi93/ProSGPV/tree/master/vignettes