Package: RiskMap 0.1.0

Emanuele Giorgi

RiskMap: Geo-Statistical Modeling of Spatially Referenced Data

Provides functions for geo-statistical analysis of both continuous and count data using maximum likelihood methods. The models implemented in the package use stationary Gaussian processes with Matern correlation function to carry out spatial prediction in a geographical area of interest. The underpinning theory of the methods implemented in the package are found in Diggle and Giorgi (2019, ISBN: 978-1-138-06102-7).

Authors:Emanuele Giorgi [aut, cre], Claudio Fronterre [ctb]

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RiskMap.pdf |RiskMap.html✨
RiskMap/json (API)

Peer review:

Bug tracker:https://github.com/claudiofronterre/riskmap/issues

On CRAN:

19 exports 1.22 score 47 dependencies 775 downloads

Last updated 3 months agofrom:d84042828e. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:create_griddist_summariesglgpmglgpm_simgpLaplace_sampling_MCMCmatern_cormatern.grad.phimatern.hessian.phimaxim.integrandplot_s_variogrampred_over_gridpred_target_gridpred_target_shppropose_utmres_variogramset_control_simto_table

Dependencies:classclassIntclicolorspaceDBIdigeste1071fansifarvergenericsggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmaxLikmgcvmiscToolsmunsellnlmepillarpkgconfigproxyR6RColorBrewerRcpprlangs2sandwichscalessfterratibbleunitsutf8vctrsviridisLitewithrwkxtablezoo