LF_Inference: Inference for linear function in high dimensional linear...

In prabrishar1/logistic: High Dimensional Inference

Description

Inference for linear function in high dimensional linear regression regression

Usage

LF_Inference(
  X,
  y,
  loading,
  lambda = NULL,
  intercept = FALSE,
  mu = NULL,
  step = NULL,
  resol = 1.5,
  maxiter = 10
)

Arguments

X	the input matrix
y	response
loading	xnew
lambda	tuning parameter
intercept	to be fitted or not
mu	tuning parameter for projection direction
step	step
resol	resolution
maxiter	maximum number of iterations

Value

linear functional inference for linear models

Examples

## Not run: 
X = matrix(sample(-2:2,100*400,replace = T),nrow=100,ncol=400)
beta = (1:400)/25
y = X%*%beta + rnorm(100,0,1)
LF_Inference(X = X, y = y, loading = c(1,rep(0,399)), intercept = TRUE)

## End(Not run)

prabrishar1/logistic documentation built on Aug. 3, 2020, 1:11 a.m.