install.packages('Rdistance')Rdistance contains functions and associated routines to analyze
distance-sampling data collected on point or line transects.
Some of Rdistance's features include:
Accommodation of both point and line transect analyses
in one routine (dfuncEstim).
Regression-like formula for inclusion of covariate in
distance functions (dfuncEstim).
Automatic bootstrap confidence intervals
(abundEstim).
Availability of both study-area and site-level abundance
estimates (abundEstim).
Classical, parametric distance functions
(halfnorm.like, hazrate.like), and
expansion functions (cosine.expansion,
hermite.expansion, simple.expansion).
Non-classic distance functions (Gamma.like,
negexp.like, uniform.like)
and a non-parametric smoother
dfuncSmu).
User defined distance functions.
Automated distance function fits and selection
autoDistSamp.
Extended vignettes.
print, plot, predict, coef,
and summary
methods for distance function objects and abundance classes.
Rdistance optimization.Rdistance contains four example datasets: two collected using a
line-transect survey (i.e., sparrowDetectionData and
sparrowSiteData) and two collected using a point-transect
(sometimes called a point count) survey (i.e.,
thrasherDetectionData and thrasherSiteData).
These datasets demonstrate the type and format of input data required by
Rdistance to estimate a detection function and abundance from
distance sampling data collected by surveying line transects or point
transects. They also allow the user to step through the tutorials described
in the package vignettes. Only the detection data is needed to fit a
detection function (if there are no covariates in the detection function;
see dfuncEstim), but both detection and
the additional site data are needed to estimate abundance (or to include
site-level covariates in the detection function; see
abundEstim).
Line transect (sparrow) data come from 72 transects, each 500 meters long,
surveyed for Brewer's Sparrows by the Wyoming Cooperative Fish & Wildlife
Research Unit in 2012.
Point transect (thrasher) data come from 120 points surveyed for Sage
Thrashers by the Wyoming Cooperative Fish & Wildlife Research Unit in 2013.
See the package vignettes for Rdistance tutorials using these
datasets.Rdistance contains four example datasets: two collected using a
line-transect survey (i.e., sparrowDetectionData and
sparrowSiteData) and two collected using a point-transect
(sometimes called a point count) survey (i.e.,
thrasherDetectionData and thrasherSiteData).
These datasets demonstrate the type and format of input data required by
Rdistance to estimate a detection function and abundance from
distance sampling data collected by surveying line transects or point
transects. They also allow the user to step through the tutorials described
in the package vignettes. Only the detection data is needed to fit a
detection function (if there are no covariates in the detection function;
see dfuncEstim), but both detection and
the additional site data are needed to estimate abundance (or to include
site-level covariates in the detection function; see
abundEstim).
Line transect (sparrow) data come from 72 transects, each 500 meters long,
surveyed for Brewer's Sparrows by the Wyoming Cooperative Fish & Wildlife
Research Unit in 2012.
Point transect (thrasher) data come from 120 points surveyed for Sage
Thrashers by the Wyoming Cooperative Fish & Wildlife Research Unit in 2013.
See the package vignettes for Rdistance tutorials using these
datasets.Rdistance contains four example datasets: two collected using a
line-transect survey (i.e., sparrowDetectionData and
sparrowSiteData) and two collected using a point-transect
(sometimes called a point count) survey (i.e.,
thrasherDetectionData and thrasherSiteData).
These datasets demonstrate the type and format of input data required by
Rdistance to estimate a detection function and abundance from
distance sampling data collected by surveying line transects or point
transects. They also allow the user to step through the tutorials described
in the package vignettes. Only the detection data is needed to fit a
detection function (if there are no covariates in the detection function;
see dfuncEstim), but both detection and
the additional site data are needed to estimate abundance (or to include
site-level covariates in the detection function; see
abundEstim).
Line transect (sparrow) data come from 72 transects, each 500 meters long,
surveyed for Brewer's Sparrows by the Wyoming Cooperative Fish & Wildlife
Research Unit in 2012.
Point transect (thrasher) data come from 120 points surveyed for Sage
Thrashers by the Wyoming Cooperative Fish & Wildlife Research Unit in 2013.
See the package vignettes for Rdistance tutorials using these
datasets.Rdistance contains four example datasets: two collected using a
line-transect survey (i.e., sparrowDetectionData and
sparrowSiteData) and two collected using a point-transect
(sometimes called a point count) survey (i.e.,
thrasherDetectionData and thrasherSiteData).
These datasets demonstrate the type and format of input data required by
Rdistance to estimate a detection function and abundance from
distance sampling data collected by surveying line transects or point
transects. They also allow the user to step through the tutorials described
in the package vignettes. Only the detection data is needed to fit a
detection function (if there are no covariates in the detection function;
see dfuncEstim), but both detection and
the additional site data are needed to estimate abundance (or to include
site-level covariates in the detection function; see
abundEstim).
Line transect (sparrow) data come from 72 transects, each 500 meters long,
surveyed for Brewer's Sparrows by the Wyoming Cooperative Fish & Wildlife
Research Unit in 2012.
Point transect (thrasher) data come from 120 points surveyed for Sage
Thrashers by the Wyoming Cooperative Fish & Wildlife Research Unit in 2013.
See the package vignettes for Rdistance tutorials using these
datasets.