markov_two_states

Constructs a <code>missingness_model</code> representing a two-state Markov process
for missing/observed indicators. The process takes values in {0, 1},
where 1 indicates observed and 0 indicates missing.

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.

Lionel Voirol

gmwmx2

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

Haotian Xu

Yuming Zhang

Luca Insolia

Roberto Molinari

Stéphane Guerrier

markov_two_states function

<dl><dt>p1</dt>
<dd>Transition probability from observed (1) to missing (0).</dd>
<dt>p2</dt>
<dd>Transition probability from missing (0) to observed (1).</dd></dl>

Arguments

Markov two-state missingness model (missingness_model) — markov_two_states

<dl>

<dt>p1</dt>
<dd>Transition probability from observed (1) to missing (0).</dd>


<dt>p2</dt>
<dd>Transition probability from missing (0) to observed (1).</dd>

</dl>

markov_two_states: Markov two-state missingness model (`missingness_model`)

Description

Usage

Value

Arguments

Examples