Package: mlrv 0.1.2

Lujia Bai

mlrv: Long-Run Variance Estimation in Time Series Regression

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)<doi:10.3150/23-BEJ1680> Zhou Zhou and Wei Biao Wu(2010)<doi:10.1111/j.1467-9868.2010.00743.x> Jianqing Fan and Wenyang Zhang<doi:10.1214/aos/1017939139> Lujia Bai and Weichi Wu(2024)<doi:10.1093/biomet/asae013> Dimitris N. Politis, Joseph P. Romano, Michael Wolf(1999)<doi:10.1007/978-1-4612-1554-7> Weichi Wu and Zhou Zhou(2018)<doi:10.1214/17-AOS1582>.

Authors:Lujia Bai [aut, cre], Weichi Wu [ctb]

mlrv_0.1.2.tar.gz
mlrv_0.1.2.tar.gz(r-4.7-arm64)mlrv_0.1.2.tar.gz(r-4.7-x86_64)mlrv_0.1.2.tar.gz(r-4.6-arm64)mlrv_0.1.2.tar.gz(r-4.6-x86_64)
mlrv_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
mlrv/json (API)

# Install 'mlrv' in R:

install.packages('mlrv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

hk_data - This is data to be included in my package

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas cpp openmp

2.00 score 5 scripts 336 downloads 15 exports 10 dependencies

Last updated from:b1d285309f. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	157
linux-devel-x86_64	OK	156
source / vignettes	OK	314
linux-release-arm64	OK	157
linux-release-x86_64	OK	136
wasm-release	OK	156

Exports:bregress2 gcv_cov heter_covariate heter_gradient Heter_LRV loc_constant LocLinear lrv_measure MV_critical MV_critical_cp MV_ise_heter_critical Qct_reg Qt_data rule_of_thumb sim_T

Dependencies:codetools doParallel foreach iterators magrittr mathjaxr numDeriv Rcpp RcppArmadillo xtable

Using mlrv to anaylze data

Rendered fromdata.Rmdusingknitr::rmarkdown

Last update: 2024-07-31
Started: 2023-11-08

Citation

Readme and manuals

Help Manual

Help page	Topics
Simulate data from time-varying time series regression model with change points	bregress2
Generalized Cross Validation	gcv_cov
Long memory tests for non-stationary time series regression	heter_covariate
Structural stability tests for non-stationary time series regression	heter_gradient
Long-run covariance matrix estimators	Heter_LRV
This is data to be included in my package	hk_data
Nonparametric smoothing	loc_constant
Local linear Regression	LocLinear
Comparing bias or mse of lrv estimators based on numerical methods	lrv_measure
Statistics-adapted values for extended minimum volatility selection.	MV_critical
Statistics-adapted values for extended minimum volatility selection.	MV_critical_cp
MV method	MV_ise_heter_critical
Simulate data from time-varying time series regression model	Qct_reg
Simulate data from time-varying trend model	Qt_data
rule of thumb interval for the selection of smoothing parameter b	rule_of_thumb
bootstrap distribution	sim_T

Package: mlrv 0.1.2

mlrv: Long-Run Variance Estimation in Time Series Regression

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)