Package: nimbleSCR 0.2.1

nimbleSCR: Spatial Capture-Recapture (SCR) Methods Using 'nimble'

Provides utility functions, distributions, and fitting methods for Bayesian Spatial Capture-Recapture (SCR) and Open Population Spatial Capture-Recapture (OPSCR) modelling using the nimble package (de Valpine et al. 2017 <doi:10.1080/10618600.2016.1172487 >). Development of the package was motivated primarily by the need for flexible and efficient analysis of large-scale SCR data (Bischof et al. 2020 <doi:10.1073/pnas.2011383117 >). Computational methods and techniques implemented in nimbleSCR include those discussed in Turek et al. 2021 <doi:10.1002/ecs2.3385>; among others. For a recent application of nimbleSCR, see Milleret et al. (2021) <doi:10.1098/rsbl.2021.0128>.

Authors:Richard Bischof [aut], Daniel Turek [aut, cre], Cyril Milleret [aut], Torbjørn Ergon [aut], Pierre Dupont [aut], Soumen Dey [aut], Wei Zhang [aut], Perry de Valpine [aut]

nimbleSCR_0.2.1.tar.gz
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nimbleSCR.pdf |nimbleSCR.html✨
nimbleSCR/json (API)
NEWS

# Install 'nimbleSCR' in R:
install.packages('nimbleSCR', repos = c('https://danielturek.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.99 score 197 scripts 253 downloads 1 mentions 69 exports 16 dependencies

Last updated 2 years agofrom:8449287983. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 23 2024
R-4.5-winNOTENov 23 2024
R-4.5-linuxNOTENov 23 2024
R-4.4-winNOTENov 23 2024
R-4.4-macNOTENov 23 2024
R-4.3-winNOTENov 23 2024
R-4.3-macNOTENov 23 2024

Exports:calcLocalTrapDistscalcLocalTrapExposurecalculateDensitycalcWindowSizesdbernppACdbernppACmovement_expdbernppACmovement_normaldbernppDetection_normaldbernppLocalACmovement_expdbernppLocalACmovement_normaldbernppLocalDetection_normaldbinom_vectordbinomLocal_expdbinomLocal_normaldbinomLocal_normalPlateaudcatState1Alive1DeaddcatState1Alive2DeaddcatState2Alive2DeaddDispersal_expdHabitatMaskdmultiLocal_normaldnormalizerdpoisLocal_normaldpoisppACdpoisppDetection_normaldpoisppLocalDetection_normalfindLocalTrapsgetHomeRangeAreagetLocalObjectsgetLocalTrapIndicesgetMidPointNodesgetNumLocalTrapsgetSparseYgetWindowCoordsgetWindowIndexintegrateIntensity_expintegrateIntensity_normalintegrateIntensityLocal_expintegrateIntensityLocal_normalmakeConstantNimbleFunctionmakeGridmarginalVoidProbIntegrandmarginalVoidProbNumIntegrationrbernppACrbernppACmovement_exprbernppACmovement_normalrbernppDetection_normalrbernppLocalACmovement_exprbernppLocalACmovement_normalrbernppLocalDetection_normalrbinom_vectorrbinomLocal_exprbinomLocal_normalrbinomLocal_normalPlateaurcatState1Alive1DeadrcatState1Alive2DeadrcatState2Alive2DeadrDispersal_exprHabitatMaskrmultiLocal_normalrnormalizerrpoisLocal_normalrpoisppACrpoisppDetection_normalrpoisppLocalDetection_normalsampler_categorical_generalscaleCoordsToHabitatGridstratRejectionSampler_expstratRejectionSampler_normal

Dependencies:clicodacpp11glueigraphlatticelifecyclemagrittrMatrixnimblenumDerivpkgconfigpracmaR6rlangvctrs

Fit with half-normal plateau detection function and home range size estimation using nimbleSCR package

Soumen Dey

Rendered fromFit_with_dbinomLocal_normalPlateau_and_HomeRangeAreaComputation.rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-09-02
Started: 2022-09-02

Point process Bayesian SCR models with nimbleSCR

Cyril Milleret, Wei Zhang, Pierre Dupont and Richard Bischof

Rendered fromPoint_Process.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-09-02
Started: 2021-10-25

Using nimbleSCR to fit 'point process SCR models' to wolverine (Gulo gulo) non-invasive genetic sampling data

Pierre Dupont

Rendered fromWolverinePointProcess.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-09-02
Started: 2022-09-02

Using nimbleSCR to simulate and fit Bayesian SCR models

Cyril Milleret

Rendered fromSimulate_and_fit_SCR_models_with_dbinomLocal_normal.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2022-09-02
Started: 2021-07-01

Wolverine Example

Cyril Milleret, Daniel Turek and Pierre Dupont

Rendered fromwolverine_example.Rmdusingknitr::rmarkdownon Nov 23 2024.

Last update: 2021-07-01
Started: 2021-07-01

Readme and manuals

Help Manual

Help pageTopics
NIMBLE function to calculate the density of individuals alive in each habitat cell.calculateDensity
Window size calculationcalcWindowSizes
Bernoulli point process for the distribution of activity centersdbernppAC rbernppAC
Bernoulli point process for activity center movement (exponential kernel)dbernppACmovement_exp rbernppACmovement_exp
Bernoulli point process for activity center movement (normal kernel)dbernppACmovement_normal rbernppACmovement_normal
Bernoulli point process detection modeldbernppDetection_normal rbernppDetection_normal
Local evaluation of a Bernoulli point process for activity center movement (exponential kernel)dbernppLocalACmovement_exp rbernppLocalACmovement_exp
Local evaluation of a Bernoulli point process for activity center movement (normal kernel)dbernppLocalACmovement_normal rbernppLocalACmovement_normal
Local evaluation for a Bernoulli point process detection modeldbernppLocalDetection_normal rbernppLocalDetection_normal
Vectorized binomial distributiondbinom_vector rbinom_vector
Local evaluation of a binomial SCR observation processdbinomLocal_exp rbinomLocal_exp
Local evaluation of a binomial SCR detection processdbinomLocal_normal rbinomLocal_normal
Local evaluation of a binomial SCR observation processdbinomLocal_normalPlateau rbinomLocal_normalPlateau
Density and random generation of a categorical distribution describing state transition with one alive and one dead states.dcatState1Alive1Dead rcatState1Alive1Dead
Density and random generation of a categorical distribution describing state transition with one alive and two dead states.dcatState1Alive2Dead rcatState1Alive2Dead
Density and random generation of a categorical distribution describing state transition with two alive and two dead states.dcatState2Alive2Dead rcatState2Alive2Dead
Bivariate exponential dispersal distribution for activity centersdDispersal_exp rDispersal_exp
Ones trick distribution for irregular habitat shapesdHabitatMask rHabitatMask
Local evaluation of a multinomial SCR detection processdmultiLocal_normal rmultiLocal_normal
Normalizing constant generatordnormalizer rnormalizer
Local evaluation of a Poisson SCR detection processdpoisLocal_normal rpoisLocal_normal
Poisson point process for the distribution of activity centersdpoisppAC rpoisppAC
Poisson point process detection modeldpoisppDetection_normal rpoisppDetection_normal
Local evaluation for a Poisson point process detection modeldpoisppLocalDetection_normal rpoisppLocalDetection_normal
Computation of home range radius and areagetHomeRangeArea
Local Objects IdentificationgetLocalObjects
Generate midpoint integration nodesgetMidPointNodes
Sparse Matrix PreparationgetSparseY
Get lower and upper windows coordinatesgetWindowCoords
Get window indexgetWindowIndex
Integrate the multivariate exponential intensityintegrateIntensity_exp
Integrate the multivariate normal intensityintegrateIntensity_normal
Integrate the multivariate normal intensity with local evaluationintegrateIntensityLocal_normal
Local Trap CalculationscalcLocalTrapDists calcLocalTrapExposure findLocalTraps getLocalTrapIndices getNumLocalTraps localTrapCalculations makeGrid
Integrand of the marginal void probability integralmarginalVoidProbIntegrand
Marginal void probabilitymarginalVoidProbNumIntegration
'nimble' MCMC sampler function for general categorial distributionssampler_categorical_general
Scale x- and y-coordinates to grid cells coordinates.scaleCoordsToHabitatGrid
Stratified rejection sampler for multivariate exponential point processstratRejectionSampler_exp
Stratified rejection sampler for multivariate normal point processstratRejectionSampler_normal