Package: gmwmx2 0.0.5

Lionel Voirol

gmwmx2: Estimate Functional and Stochastic Parameters of Linear Models with Correlated Residuals and Missing Data

Implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Voirol, L., Xu, H., Zhang, Y., Insolia, L., Molinari, R. and Guerrier, S. (2024) <doi:10.48550/arXiv.2409.05160>. The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals in presence of missing data. The 'gmwmx2' package provides functions to load and plot Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory and functions to estimate linear model model with correlated residuals in presence of missing data.

Authors:Lionel Voirol [aut, cre], Haotian Xu [aut], Yuming Zhang [aut], Luca Insolia [aut], Roberto Molinari [aut], Stéphane Guerrier [aut]

gmwmx2_0.0.5.tar.gz
gmwmx2_0.0.5.zip(r-4.7)gmwmx2_0.0.5.zip(r-4.6)gmwmx2_0.0.5.zip(r-4.5)
gmwmx2_0.0.5.tgz(r-4.6-x86_64)gmwmx2_0.0.5.tgz(r-4.6-arm64)gmwmx2_0.0.5.tgz(r-4.5-x86_64)gmwmx2_0.0.5.tgz(r-4.5-arm64)
gmwmx2_0.0.5.tar.gz(r-4.7-arm64)gmwmx2_0.0.5.tar.gz(r-4.7-x86_64)gmwmx2_0.0.5.tar.gz(r-4.6-arm64)gmwmx2_0.0.5.tar.gz(r-4.6-x86_64)
gmwmx2_0.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gmwmx2/json (API)
NEWS

# Install 'gmwmx2' in R:
install.packages('gmwmx2', repos = c('https://smac-group.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/smac-group/gmwmx2/issues

Pkgdown/docs site:https://smac-group.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

5.91 score 2 stars 17 scripts 526 downloads 13 exports 43 dependencies

Last updated from:73fd0d3001. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK201
linux-devel-x86_64OK205
source / vignettesOK1141
linux-release-arm64OK201
linux-release-x86_64OK211
macos-release-arm64OK222
macos-release-x86_64OK339
macos-oldrel-arm64OK168
macos-oldrel-x86_64OK524
windows-develOK205
windows-releaseOK248
windows-oldrelOK174
wasm-releaseOK152

Exports:ar1download_all_stations_ngldownload_estimated_velocities_ngldownload_station_nglflickergenerategmwm2gmwmx2markov_two_statesmaternplrwwn

Dependencies:askpassbackportsbroomclicodacpp11curldata.tabledplyrfarvergenericsgluehttr2labelinglatticelifecyclelongmemomagrittrMatrixopensslpillarpkgconfigpurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangrobcorscalessimtsstringistringrsystibbletidyrtidyselectutf8vctrsviridisLitewithrwv

Data generation

Rendered fromdata_generation.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-18
Started: 2026-02-05

Estimate a small network of GNSS stations

Rendered fromestimate_small_network.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-18
Started: 2024-11-15

Estimate composite stochastic processes

Rendered fromestimate_composite_stochastic_models.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-19
Started: 2026-02-07

Estimate geodetic time series from the Nevada Geodetic Laboratory

Rendered fromestimate_geodetic_time_series_from_ngl.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-19
Started: 2026-02-17

GMWMX: Estimate linear models with dependent errors

Rendered fromestimate_linear_models_with_dependent_errors.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-19
Started: 2026-02-18

GMWMX: Estimate linear models with dependent errors and missing observations

Rendered fromestimate_linear_models_with_dependent_errors_and_missing_observations.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-19
Started: 2026-02-18

Load and plot data from Nevada Geodetic Laboratory

Rendered fromload_plot_data_ngl.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-18
Started: 2024-11-05

Plot a large network of GNSS data

Rendered fromplot_large_network.Rmdusingknitr::rmarkdownon May 20 2026.

Last update: 2026-02-18
Started: 2024-11-15

Readme and manuals

Help Manual

Help pageTopics
Add to a 'sum_model' object+.sum_model
Add to a 'time_series_model' object+.time_series_model
AR(1) process ('time_series_model')ar1
Estimated northward and eastward velocity and their standard deviation using the GMWMX estimatordf_estimated_velocities_gmwmx
Download all stations name and location from the Nevada Geodetic Laboratorydownload_all_stations_ngl
Download estimated velocities using the MIDAS estimator provided by the Nevada Geodetic Laboratory for all stations.download_estimated_velocities_ngl
Download GNSS position time series and steps reference from the Nevada Geodetic Laboratory with IGS14 or IGS20 reference frame.download_station_ngl
Flicker noise process ('time_series_model')flicker
Generate a time series from a 'time_series_model' or 'sum_model' objectgenerate
GMWM estimatorgmwm2
GMWMX estimatorgmwmx2 gmwmx2.default gmwmx2.gnss_ts_ngl
Markov two-state missingness model ('missingness_model')markov_two_states
Matern process ('time_series_model')matern
Stationary Power-Law process ('time_series_model')pl
Plot a 'generated_composite_model_time_series' objectplot.generated_composite_model_time_series
Plot a 'generated_missingness' objectplot.generated_missingness
Plot a 'generated_time_series' objectplot.generated_time_series
Plot method for a 'gmwm2_fit' objectplot.gmwm2_fit
Plot a 'gmwmx2_fit_gnss_ts_ngl' objectplot.gmwmx2_fit_gnss_ts_ngl
Plot a 'gnss_ts_ngl' objectplot.gnss_ts_ngl
Print method for a 'gmwm2_fit' objectprint.gmwm2_fit
Print method for a 'gmwmx2_fit' objectprint.gmwmx2_fit
Print method for a 'gmwmx2_fit_gnss_ts_ngl' objectprint.gmwmx2_fit_gnss_ts_ngl
Random walk process ('time_series_model')rw
White noise process ('time_series_model')wn