Package: cocons 0.1.5

cocons: Covariate-Based Covariance Functions for Nonstationary Spatial Modeling

Estimation, prediction, and simulation of nonstationary Gaussian process with modular covariate-based covariance functions. Sources of nonstationarity, such as spatial mean, variance, geometric anisotropy, smoothness, and nugget, can be considered based on spatial characteristics. An induced compact-supported nonstationary covariance function is provided, enabling fast and memory-efficient computations when handling densely sampled domains.

Authors:Federico Blasi [aut, cre], Reinhard Furrer [ctb]

cocons_0.1.5.tar.gz
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cocons_0.1.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cocons/json (API)

# Install 'cocons' in R:

install.packages('cocons', repos = c('https://blasif.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/blasif/cocons/issues

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

holes - Holes Data Set
holes_bm - Holes with trend + multiple realizations Data Set
stripes - Stripes Data Set

On CRAN:

covariance-matrix cpp estimation gaussian-processes large-dataset nonstationarity optimization prediction simulation cpp

4.30 score 4 stars 2 scripts 306 downloads 39 exports 14 dependencies

Last updated from:74229283c7. Checks:13 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	2005
linux-devel-x86_64	WARNING	213
source / vignettes	OK	229
linux-release-arm64	WARNING	1957
linux-release-x86_64	WARNING	244
macos-release-arm64	WARNING	179
macos-release-x86_64	WARNING	429
macos-oldrel-arm64	WARNING	238
macos-oldrel-x86_64	WARNING	656
windows-devel-arm64	WARNING	386
windows-devel-x86_64	WARNING	238
windows-release-arm64	WARNING	375
windows-release-x86_64	WARNING	204
windows-oldrel-x86_64	WARNING	206
wasm-release	OK	139

Exports:coco cocoOptim cocoPredict cocoSim cov_rns cov_rns_classic cov_rns_pred cov_rns_taper cov_rns_taper_pred getAIC getBIC getBoundaries getBoundariesV2 getBoundariesV3 getBoundariesV4 getCIs getCovMatrix getCRPS getDensityFromDelta getDesignMatrix getEstims getHessian getLoglik getLogScore getModelLists getModHess GetNeg2loglikelihood GetNeg2loglikelihoodProfile GetNeg2loglikelihoodREML GetNeg2loglikelihoodTaper GetNeg2loglikelihoodTaperProfile getScale getSpatEffects getSpatMean is.formula plot plotOptimInfo summary sumsmoothlone

Dependencies:BH dotCall64 evaluate fields highr knitr maps optimParallel RColorBrewer Rcpp spam viridisLite xfun yaml

cocons-vignette

Rendered fromcocons.Rnwusingutils::Sweave

Last update: 2024-07-22
Started: 2024-07-22

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Covariate-based Covariance Functions for Nonstationary Gaussian Processes	cocons-package cocons
Creates a coco S4 object	coco
An S4 class to store information	coco-class
Optimizer for coco objects	cocoOptim
Prediction for coco objects	cocoPredict
Marginal and conditional simulation of nonstationary Gaussian processes	cocoSim
Dense covariance function (difference parameterization)	cov_rns
Dense covariance function (classic parameterization)	cov_rns_classic
Dense covariance function	cov_rns_pred
Sparse covariance function	cov_rns_taper
Sparse covariance function	cov_rns_taper_pred
Retrieve AIC	getAIC
Retrieve BIC	getBIC
Simple build of boundaries	getBoundaries
Simple build of boundaries (v2)	getBoundariesV2
Simple build of boundaries (v3)	getBoundariesV3
Simple build of boundaries	getBoundariesV4
Compute approximate confidence intervals for a coco object	getCIs
Covariance matrix for "coco" class	getCovMatrix
Based on a set of predictions computes the Continuous Ranked Probability Score	getCRPS
Based on a specific taper scale (delta), retrieves the density of the covariance matrix.	getDensityFromDelta
Create an efficient design matrix based on a list of aspect models	getDesignMatrix
Retrieve estimates from a fitted coco object	getEstims
getHessian	getHessian
Retrieve the loglikelihood value	getLoglik
Based on a set of predictions computes the Log-Score	getLogScore
Builds the necessary input for building covariance matrices	getModelLists
Retrieves the modified inverse of the hessian	getModHess
GetNeg2loglikelihood	GetNeg2loglikelihood
GetNeg2loglikelihoodProfile	GetNeg2loglikelihoodProfile
GetNeg2loglikelihoodREML	GetNeg2loglikelihoodREML
GetNeg2loglikelihoodTaper	GetNeg2loglikelihoodTaper
GetNeg2loglikelihoodTaperProfile	GetNeg2loglikelihoodTaperProfile
Fast and simple standardization for the design matrix.	getScale
Evaluates the spatially-varying functions from a coco object at locs	getSpatEffects
Computes the spatial mean of a (fitted) coco object	getSpatMean
Holes Data Set	holes
Holes with trend + multiple realizations Data Set	holes_bm
check whether an R object is a formula	is.formula
Plot Method for coco objects	plot,coco,missing-method plot,coco-method
Plot log info detailed	plotOptimInfo
Show Method for Coco Class	show show,coco-method
Stripes Data Set	stripes
Summary Method for Coco Class	summary summary,coco-method
smoothed-L1 penalization over the covariate-driven parameters	sumsmoothlone