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mlrv (version 0.1.2)

Long-Run Variance Estimation in Time Series Regression

Description

Plug-in and difference-based long-run covariance matrix estimation for time series regression. Two applications of hypothesis testing are also provided. The first one is for testing for structural stability in coefficient functions. The second one is aimed at detecting long memory in time series regression. Lujia Bai and Weichi Wu (2024) Zhou Zhou and Wei Biao Wu(2010) Jianqing Fan and Wenyang Zhang Lujia Bai and Weichi Wu(2024) Dimitris N. Politis, Joseph P. Romano, Michael Wolf(1999) Weichi Wu and Zhou Zhou(2018).

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Version

Install

install.packages('mlrv')

Monthly Downloads

161

Version

0.1.2

License

MIT + file LICENSE

Maintainer

Lujia Bai

Last Published

July 30th, 2024

Functions in mlrv (0.1.2)

lrv_measure

Comparing bias or mse of lrv estimators based on numerical methods
mlrv-package

mlrv: Long-Run Variance Estimation in Time Series Regression
rule_of_thumb

rule of thumb interval for the selection of smoothing parameter b
loc_constant

Nonparametric smoothing
Heter_LRV

Long-run covariance matrix estimators
Qt_data

Simulate data from time-varying trend model
MV_critical

Statistics-adapted values for extended minimum volatility selection.
MV_critical_cp

Statistics-adapted values for extended minimum volatility selection.
heter_gradient

Structural stability tests for non-stationary time series regression
gcv_cov

Generalized Cross Validation
heter_covariate

Long memory tests for non-stationary time series regression
LocLinear

Local linear Regression
hk_data

This is data to be included in my package
bregress2

Simulate data from time-varying time series regression model with change points
Qct_reg

Simulate data from time-varying time series regression model
MV_ise_heter_critical

MV method
sim_T

bootstrap distribution