Package: mads 0.1.6

Laura Marshall

mads: Multi-Analysis Distance Sampling

Performs distance sampling analyses on a number of species at once and can account for unidentified sightings, model uncertainty and covariate uncertainty. Unidentified sightings refer to sightings which cannot be allocated to a single species but may instead be allocated to a group of species. The abundance of each unidentified group is estimated and then prorated to the species estimates. Model uncertainty should be incorporated when multiple models give equally good fit to the data but lead to large differences in estimated density / abundance. Covariate uncertainty should be incorporated when covariates cannot be measured accurately, for example this is often the case for group size in marine mammal surveys. Variance estimation for these methods is via a non parametric bootstrap. The methods implemented are described in Gerodette T. and Forcada J. (2005) <10.3354/meps291001> Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean.

Authors:Laura Marshall

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NEWS

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

Peer review:

Bug tracker:https://github.com/distancedevelopment/mads/issues

Datasets:
  • mads.data - Example simulated data used to demonstrate the package functionality

On CRAN:

2.30 score 2 stars 2 scripts 97 downloads 1 exports 11 dependencies

Last updated 12 months agofrom:d3f9e9979e. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 18 2024
R-4.5-winOKOct 18 2024
R-4.5-linuxOKOct 18 2024
R-4.4-winOKOct 18 2024
R-4.4-macOKOct 18 2024
R-4.3-winOKOct 18 2024
R-4.3-macOKOct 18 2024

Exports:execute.multi.analysis

Dependencies:latticeMatrixmgcvmrdsnlmenloptrnumDerivoptimxpracmaRsolnptruncnorm

Readme and manuals

Help Manual

Help pageTopics
Multi-Analysis Distance Sampling (mads)mads-package mads
Enters the prorated results into the bootstrap.results arrayaccumulate.results
Calculates the abundance for each species code including the unidentified codes if supplied.calculate.dht
Checks whether the model has convergedcheck.convergence
Checks whether the model's fitted values make sensecheck.fitted
Creates a subsetted observation tablecreate.obs.table
Creates a list of arrays for storing the ddf resultscreate.param.arrays
Creates a list of arrays for storing the dht resultscreate.result.arrays
Performs Multiple Analyses on Distance Dataexecute.multi.analysis
Refits the detection functions to the resampled datafit.ddf.models
Formats the estimated abundances of all species categories, to be consistent with the prorated results.format.dht.results
Example simulated data used to demonstrate the package functionalitymads.data
Warning functionmae.warning
Extracts the model descriptionmodel.description
Summarises the bootstrap results.process.bootstrap.results
Summarises warningsprocess.warnings
Prorate the estimated abundances of the unidentified sightings to the other identified species categories.prorate.unidentified
Randomly generates values from a zero-truncated Poisson distributionrtpois
Summary of multi-analysis objectsummary.ma
Summary of multi-analysis objectsummary.ma.allspecies
Summary of multi-analysis objectsummary.ma.allunid
Summary of multi-analysis objectsummary.ma.analysis
Print a summary of an element of a multi-analysis result corresponding to a single species included in the analyses.summary.ma.species
Summary of multi-analysis objectsummary.ma.unid