mads.data: Example simulated data used to demonstrate the package...
In mads: Multi-Analysis Distance Sampling
Description
These data were generated using DSsim. Two populations were generated inside
a rectangular study region, one of these is called 'CD' (common dolphin) and the
other is 'WSD' (white-sided dolphin). Density was assumed to be equal across the
study area and the population sizes for the CD and WSD populations were 3000
and 1500, respectively. Detections of individuals were simulated based on half
normal detection functions with a scale parameter of 0.5 and a truncation
distance of 1. A systematic parallel line transect design was used. Once both
sets of data had been generated they were combined and 10
randomly selected to be in the unidentified sightings category.
Format
This is a list of 4 items. The first is dist.data a dataframe with
distance sampling data including the columns object, transect.ID, distance,
x, y, true.species, unid, species, observer. The other items are the
region, sample and observations tables as per the definitions in mrds.
mads documentation built on July 2, 2020, 2:12 a.m.
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Description
These data were generated using DSsim. Two populations were generated inside a rectangular study region, one of these is called 'CD' (common dolphin) and the other is 'WSD' (white-sided dolphin). Density was assumed to be equal across the study area and the population sizes for the CD and WSD populations were 3000 and 1500, respectively. Detections of individuals were simulated based on half normal detection functions with a scale parameter of 0.5 and a truncation distance of 1. A systematic parallel line transect design was used. Once both sets of data had been generated they were combined and 10 randomly selected to be in the unidentified sightings category.
Format
This is a list of 4 items. The first is dist.data a dataframe with distance sampling data including the columns object, transect.ID, distance, x, y, true.species, unid, species, observer. The other items are the region, sample and observations tables as per the definitions in mrds.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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