adalasso: Implement Adaptive Lasso via glmnet

In zhan-gao/LasForecast: Time series linear predictive regression

Implement Adaptive Lasso via glmnet

Description

Estimation function. Tuning parameter inputs needed.
Incorporates both high-dim(Lasso as initial estimator) and low-dim (OLS as initial estimator).

Usage

adalasso(
  x,
  y,
  lambda,
  lambda_lasso = NULL,
  gamma = 1,
  intercept = TRUE,
  scalex = FALSE
)

Arguments

x	Predictor matrix (n-by-p matrix)
y	Response variable
lambda	Shrinkage tuning parameter for the adaptive step
lambda_lasso	Shrinkage tuning parater for the initial step Lasso estimation (If applicable)
gamma	Parameter controlling the inverse of first step estimate
intercept	A boolean: include an intercept term or not
scalex	A boolean: standardize the design matrix or not

Value

A list contains estimated intercept and slope

ahat	Estimated intercept
bhat	Estimated slope

Examples

adalasso(x,y)

zhan-gao/LasForecast documentation built on Sept. 18, 2024, 9:40 p.m.