RcppCensSpatial

It provides functions to estimate parameters in linear spatial models with censored/missing responses via the Expectation-Maximization (EM), the Stochastic Approximation EM (SAEM), or the Monte Carlo EM (MCEM) algorithm. These algorithms are widely used to compute the maximum likelihood (ML) estimates in problems with incomplete data. The EM algorithm computes the ML estimates when a closed expression for the conditional expectation of the complete-data log-likelihood function is available. In the MCEM algorithm, the conditional expectation is substituted by a Monte Carlo approximation based on many independent simulations of the missing data. In contrast, the SAEM algorithm splits the E-step into simulation and integration steps. This package also approximates the standard error of the estimates using the Louis method. Moreover, it has a function that performs spatial prediction in new locations.

Last 30 days

This package has been downloaded 216 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 13 times.

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Last 365 days

This package has been downloaded 2,387 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jan 03, 2025 with 46 downloads.

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