Reference

Composite stochastic models and simulation
wn()	White noise process (time_series_model)
ar1()	AR(1) process (time_series_model)
pl()	Stationary Power-Law process (time_series_model)
matern()	Matern process (time_series_model)
rw()	Random walk process (time_series_model)
flicker()	Flicker noise process (time_series_model)
`+`(<time_series_model>)	Add to a time_series_model object
`+`(<sum_model>)	Add to a sum_model object
generate()	Generate a time series from a time_series_model or sum_model object
plot(<generated_time_series>)	Plot a generated_time_series object
plot(<generated_composite_model_time_series>)	Plot a generated_composite_model_time_series object
markov_two_states()	Markov two-state missingness model (missingness_model)
plot(<generated_missingness>)	Plot a generated_missingness object
Estimate composite stochastic models
gmwm2()	GMWM estimator
print(<gmwm2_fit>)	Print method for a gmwm2_fit object
plot(<gmwm2_fit>)	Plot method for a gmwm2_fit object
Estimate regression model with dependent errors
gmwmx2()	GMWMX estimator
print(<gmwmx2_fit>)	Print method for a gmwmx2_fit object
print(<gmwmx2_fit_gnss_ts_ngl>)	Print method for a gmwmx2_fit_gnss_ts_ngl object
plot(<gmwmx2_fit_gnss_ts_ngl>)	Plot a gmwmx2_fit_gnss_ts_ngl object
Load and plot NGL data
download_station_ngl()	Download GNSS position time series and steps reference from the Nevada Geodetic Laboratory with IGS14 or IGS20 reference frame.
plot(<gnss_ts_ngl>)	Plot a gnss_ts_ngl object
download_all_stations_ngl()	Download all stations name and location from the Nevada Geodetic Laboratory
download_estimated_velocities_ngl()	Download estimated velocities using the MIDAS estimator provided by the Nevada Geodetic Laboratory for all stations.
Data
df_estimated_velocities_gmwmx	Estimated northward and eastward velocity and their standard deviation using the GMWMX estimator