sbd: Size Biased Distributions
In sbd: Size Biased Distributions
sbd R Documentation
Size Biased Distributions
Description
Fitting and plotting parametric or non-parametric size-biased
non-negative distributions, with optional covariates in the case of
parametric. Supports three parametric options, log-normal, Weibull, and gamma.
Details
The core function is sbm, which fits a model to
non-negative observations to estimate the average of the underlying
distribution assuming that the probability of making an observation is
proportional to the size of that observation. The default gives a
non-parametric fit (the harmonic mean), and three parametric options are
also available: log-normal, Weibull, and gamma. Covariates can be included
in parametric models. The output is a list of class sbm, which has
methods plot, predict, summary, and AIC. The
functions were developed to support the analysis of speed observations from
camera trap data described by Rowcliffe et al. (2016).
Author(s)
Maintainer: Marcus Rowcliffe marcus.rowcliffe@ioz.ac.uk
References
Patil, G. P. 2002 Weighted distributions. Pp. 2369–2377 in A.H. El-Shaarawi,
W. W. Piegorsch, eds. Encycolpedia of Environmetrics. Wiley, Chichester.
Rowcliffe, J.M., Jansen, P.A., Kays, R., Kranstauber, B., and
Carbone, C. (2016). Wildlife speed cameras: measuring animal travel speed
and day range using camera traps. Remote Sensing in Ecology and
Conservation 2, 84-94.
See Also
Useful links:
sbd documentation built on June 22, 2024, 9:50 a.m.
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.
| sbd | R Documentation |
Size Biased Distributions
Description
Fitting and plotting parametric or non-parametric size-biased non-negative distributions, with optional covariates in the case of parametric. Supports three parametric options, log-normal, Weibull, and gamma.
Details
The core function is sbm, which fits a model to
non-negative observations to estimate the average of the underlying
distribution assuming that the probability of making an observation is
proportional to the size of that observation. The default gives a
non-parametric fit (the harmonic mean), and three parametric options are
also available: log-normal, Weibull, and gamma. Covariates can be included
in parametric models. The output is a list of class sbm, which has
methods plot, predict, summary, and AIC. The
functions were developed to support the analysis of speed observations from
camera trap data described by Rowcliffe et al. (2016).
Author(s)
Maintainer: Marcus Rowcliffe marcus.rowcliffe@ioz.ac.uk
References
Patil, G. P. 2002 Weighted distributions. Pp. 2369–2377 in A.H. El-Shaarawi, W. W. Piegorsch, eds. Encycolpedia of Environmetrics. Wiley, Chichester.
Rowcliffe, J.M., Jansen, P.A., Kays, R., Kranstauber, B., and Carbone, C. (2016). Wildlife speed cameras: measuring animal travel speed and day range using camera traps. Remote Sensing in Ecology and Conservation 2, 84-94.
See Also
Useful links:
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.