StempCens-package {StempCens}R Documentation

Spatio-Temporal Estimation and Prediction for Censored/Missing Responses

Description

It estimates the parameters of spatio-temporal models with censored or missing data using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic approximation of the widely used EM algorithm and is particularly valuable for models in which the E-step lacks a closed-form expression. It also provides a function to compute the observed information matrix using the method developed by Louis (1982). To assess the performance of the fitted model, case-deletion diagnostics are provided.

Details

The functions provided are:

- CovarianceM: computes the spatio-temporal covariance matrix for balanced data.

- EffectiveRange: computes the effective range for an isotropic spatial correlation function.

- EstStempCens: returns the maximum likelihood estimates of the unknown parameters.

- PredStempCens: performs spatio-temporal prediction in a set of new S spatial locations for fixed time points.

- CrossStempCens: performs cross-validation, which measure the performance of the predictive model on new test dataset.

- DiagStempCens: returns measures and graphics for diagnostic analysis.

Author(s)

Larissa A. Matos (ORCID), Katherine L. Valeriano (ORCID) and Victor H. Lachos (ORCID)

Maintainer: Larissa A. Matos (larissa.amatos@gmail.com).

References

Cook R (1977). “Detection of influential observation in linear regression.” Technometrics, 19(1), 15–18. doi:10.1080/00401706.1977.10489493.

Delyon B, Lavielle M, Moulines E (1999). “Convergence of a stochastic approximation version of the EM algorithm.” Annals of Statistics, 27(1), 94–128. doi:10.1214/aos/1018031103.

Louis T (1982). “Finding the observed information matrix when using the EM algorithm.” Journal of the Royal Statistical Society: Series B (Methodological), 44(2), 226–233. doi:10.1111/j.2517-6161.1982.tb01203.x.

Zhu H, Lee S, Wei B, Zhou J (2001). “Case-deletion measures for models with incomplete data.” Biometrika, 88(3), 727–737. doi:10.1093/biomet/88.3.727.


[Package StempCens version 1.2.0 Index]