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CensSpatial (version 3.6)

Censored Spatial Models

Description

It fits linear regression models for censored spatial data. It provides different estimation methods as the SAEM (Stochastic Approximation of Expectation Maximization) algorithm and seminaive that uses Kriging prediction to estimate the response at censored locations and predict new values at unknown locations. It also offers graphical tools for assessing the fitted model. More details can be found in Ordonez et al. (2018) .

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Version

Install

install.packages('CensSpatial')

Monthly Downloads

298

Version

3.6

License

GPL (>= 2)

Maintainer

Alejandro Ordonez

Last Published

January 24th, 2023

Functions in CensSpatial (3.6)

algnaive12

Naive 1 and Naive 2 method for spatial prediction.
depth

Depths of a geological horizon.
rspacens

Censored Spatial data simulation
Seminaive

Seminaive algorithm for spatial censored prediction.
predSCL

Prediction for the SAEM algorithm for censored spatial data.
predgraphics

Prediction graphics for SAEM Algortihm for censored spatial data.
Missouri

TCDD concentrations in Missouri (1971).
SAEMSCL

SAEM Algorithm estimation for censored spatial data.
summary.naive

Summary of a naive object
derivQfun

Maximum Likelihood Expectation (\(logQ\) function and its derivates)
derivcormatrix

First and second derivates of some correlation matrix
summary.SAEMSpatialCens

Summary of a SAEMSpatialCens object.
summary.seminaive

Summary of a seminaive object
distmatrix

Distance matrix
localinfmeas

Local influence measures.