gmwmx v.1.0.3

gmwmx version 1.0.3

• Minor modification of the acknowledgements.
• Extend documentation.
• Add support for point estimates for the GMWMX-1 for model that includes a Random Walk in the stochastic model.
• Add reference to doi: 10.1007/s00190-023-01702-8.
• Change number of decimals for std of functional parameters in print.gnsstsmodel.

v.1.0.2

Update gmwmx version 1.0.2

• Modified how is inverted the Sigma matrix in estimate_gmwmx() by now using ltsa::TrenchInverse to exploit toeplitz structure of the matrix.

• Modified how is computed the Wavelet Variance of the GLS residuals to be performed on the available wavelets coefficients in presence of missing observations in the function estimate_gmwmx().

• Corrected bug in estimate_hector() that led to non-existent names for the vector of estimated functional parameters, causing problems when printing the estimated model.

• Corrected bug in estimate_hector() that provided the wrong value FullCov to the argument LikelihoodMethod for Hector ctl file. The default is now set to AmmarGrag and the user can specify it with the new argument likelihood_method of the function estimate_hector().

gmwmx v1.0.0

The gmwmx R package implement the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) introduced in Cucci et al. (2022). The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals. The gmwmx package provides functions to estimate, compare and analyze models, utilities to load and work with Global Navigation Satellite System (GNSS) data as well as methods to compare results with the Maximum Likelihood Estimator (MLE) implemented in Hector.