Distance is a simple way to fit detection functions and estimate
abundance using distance sampling methodology.
Details
Underlying Distance is the package mrds, for more advanced
analyses (such as those involving double observer surveys) one may find it
necessary to use mrds.
Examples of distance sampling analyses are available at http://examples.distancesampling.org/.
For help with distance sampling and this package, there is a Google Group https://groups.google.com/forum/#!forum/distance-sampling.
Bugs can be reported at https://github.com/DistanceDevelopment/Distance/issues.
References
"_PACKAGE"
Key References:
Miller D.L., E. Rexstad, L. Thomas, L. Marshall and J.L. Laake. 2019. Distance Sampling in R. Journal of Statistical Software, 89(1), 1-28. doi:10.18637/jss.v089.i01
Background References:
Laake, J.L. and D.L. Borchers. 2004. Methods for incomplete detection at distance zero. In: Advanced Distance Sampling, eds. S.T. Buckland, D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. Oxford University Press.
Marques, F.F.C. and S.T. Buckland. 2004. Covariate models for the detection function. In: Advanced Distance Sampling, eds. S.T. Buckland, D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. Oxford University Press.
Author
David L. Miller dave@ninepointeightone.net