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) Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean.


mads 0.1.5

Bug Fixes

  • Fixed bug in the call to repeat fitting of the detection functions by ddf in mrds. Previously, information such as whether the data were point transect, binned, left-truncated etc. was lost from the ddf object and may have caused dht to produce incorrect estimates of abundance / density. The default options of line transects with exact distances will not have been affected.

mads 0.1.4


  • Bug fix for warnings
  • Catches the case when fitted values in ddf are 0
  • Updated package structure

mads 0.1.3


  • See notes from version 0.1.1

New Features

  • The user may now specify which field gives the species code rather than it being fixed as 'species'

mads 0.1.2


  • See notes from version 0.1.1

New Features

  • Improved system of warning messages compatible with Distance 7

mads 0.1.1


  • These methods were designs to replicate the analyses of those in Gerrodette and Forcada (2005) Currently we are still in the testing phase to ensure the methods in mads match those of Gerrodette and Forcada Our pro-rating methods for individuals are the same, but in addition we also pro-rate clusters. We do not perform model averaging only model selection at each iteration. There may be small differences in how covariate uncertainty is incorporated.

    Gerodette, T. and Forcada, J. 2005. Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean. Marine Ecology Progress Series 291:1-21.

New Features

  • Added example code

Bug Fixes

  • Changed @S3method to @export
  • Check to make sure that only ds models are input
  • Updated documentation

Reference manual

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0.1.6 by Laura Marshall, 2 years ago

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Browse source code at

Authors: Laura Marshall

Documentation:   PDF Manual  

GPL (>= 2) license

Depends on mrds, stats

Suggests testthat

See at CRAN