`gmwmx`

Overview
The `gmwmx`

`R`

package implement the
Generalized Method of Wavelet Moments with Exogenous Inputs estimator
(GMWMX) introduced in Cucci, D. A., Voirol,
L., Kermarrec, G., Montillet, J. P., and Guerrier, S. (2022) and
provides functions to estimate times series models that can be expressed
as linear models with correlated residuals. Moreover, the
`gmwmx`

package provides tools to compare and analyze
estimated models and methods to easily compare results with the Maximum
Likelihood Estimator (MLE) implemented in Hector, allowing to replicate
the examples and simulations considered in Cucci, D. A., Voirol,
L., Kermarrec, G., Montillet, J. P., and Guerrier, S. (2022). In
particular, this package implements a statistical inference framework
for the functional and stochastic parameters of models such as those
used to model Global Navigation Satellite System (GNSS) observations,
enabling the comparison of the proposed method to the standard MLE
estimates implemented in Hector.

Find the package vignettes and user’s manual at the package website.

Below are instructions on how to install and make use of the
`gmwmx`

package.

The `gmwmx`

package is available on both CRAN and GitHub.
The CRAN version is considered stable while the GitHub version is
subject to modifications/updates which may lead to installation problems
or broken functions. You can install the stable version of the
`gmwmx`

package with:

`install.packages("gmwmx")`

For users who are interested in having the latest developments, the
GitHub version is ideal although more dependencies are required to run a
stable version of the package. Most importantly, users
**must** have a (`C++`

) compiler installed on
their machine that is compatible with R (e.g. `Clang`

).

```
# Install dependencies
install.packages(c("devtools"))
# Install/Update the package from GitHub
::install_github("SMAC-Group/gmwmx")
devtools
# Install the package with Vignettes/User Guides
::install_github("SMAC-Group/gmwmx", build_vignettes = TRUE) devtools
```

`Hector`

In order to runs successfully functions that execute
`Hector`

, we assume that `Hector`

is installed and
available in the `PATH`

of the installation where these
functions are called. More precisely, when running either
`estimate_hector()`

, `remove_outliers_hector()`

,
`PBO_get_station()`

or `PBO_get_offsets()`

, we
assume that `Hector`

’s binaries executable
`estimatetrend`

, `removeoutliers`

and
`date2mjd`

are located in a folder available in the
`PATH`

by `R`

.

In order to make sure that these functions are available in the
`PATH`

, you can run `Sys.getenv("PATH")`

and
ensure that the directory that contains the executable binaries of
`Hector`

is listed in the `PATH`

.

For Linux users that are on distributions supported by
`Hector`

, this can be easily done by:

- Downloading
`Hector`

’s binaries for the corresponding OS here. - Extracting the downloaded executable binaries and saving them in a
folder, say
`$HOME/app/hector/bin`

. - Adding this folder to the system-wide
`PATH`

environment variable by modifying`/etc/environment`

. - Ensuring that the corresponding folder is accessible by
`R`

with`Sys.getenv("PATH")`

after running the script and reassigning the new`PATH`

to the`PATH`

environment variable with`. /etc/environment`

or equivalently with`source /etc/environment`

.

```
> Sys.getenv("PATH")
[1] "$HOME/app/hector/bin:..."
```

Some users have reported that the procedure described above did not
work on their installation and that even after completing these steps,
the path containing the executable binaries of `Hector`

was
not accessible to the `PATH`

recognized by `R`

. In
this case, a strategy that seems to work is to directly indicate the
path where `Hector`

is located by executing the following
command before executing a function that runs `Hector`

:

`Sys.setenv(PATH = "$HOME/app/hector/bin") `

where `"$HOME/app/hector/bin"`

is the path where are
located `Hector`

’s binaries.

`R`

librariesThe `gmwmx`

package relies on a limited number of external
libraries, but notably on `Rcpp`

and
`RcppArmadillo`

which require a `C++`

compiler for
installation, such as for example `gcc`

.

`MATLAB`

environmentIt is possible to execute functions from the `gmwmx`

`R`

package directly from a `MATLAB`

environment
and to save estimated models in the `MATLAB`

environment
thanks to `Rcall`

. `Rcall`

is an
interface which runs in `MATLAB`

and provides direct access
to methods and software packages implemented in `R`

. Refer to
issue #1 for
the detailed procedure and to the official `Rcall`

project for support.

This source code is released under is the GNU AFFERO GENERAL PUBLIC LICENSE (AGPL) v3.0.

We thank Dr. Machiel Bos for his helpful advises and constructive
comments that helped us to improve the implementation of the
`gmwmx`

package and to ensure the correct integration of
`Hector`

into the `gmwmx`

`R`

package.

Cucci, D. A., Voirol, L., Kermarrec, G., Montillet, J. P., & Guerrier, S. (2023). The Generalized Method of Wavelet Moments with eXogenous inputs: a fast approach for the analysis of GNSS position time series. Journal of Geodesy, 97(2), 14.

Guerrier, S., Skaloud, J., Stebler, Y. and Victoria-Feser, M.P., 2013. Wavelet-variance-based estimation for composite stochastic processes. Journal of the American Statistical Association, 108(503), pp.1021-1030.