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DSpat (version 0.1.5)
Spatial modelling for distance sampling data
Description
Provides functions for fitting spatial models to line transect sampling data and to estimate abundance within a region.
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0.1.6
0.1.5
0.1.1
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Install
install.packages('DSpat')
Monthly Downloads
35
Version
0.1.5
License
GPL (>= 2)
Maintainer
Jeff Laake
Last Published
November 7th, 2012
Functions in DSpat (0.1.5)
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simCovariates
Simulates covariates for an example in DSpat
weeds.all
Dubbo weed data with constructed y-coordinate
integrate.intensity
Integrated intensity of fitted model
weeds.obs
Observations from Dubbo weed data
quadscheme.lt
Create line transect quadrature for spatstat
weeds.lines
Transect lines from Dubbo weed data
weeds.covariates
Covariate grid for Dubbo weed data
create.covariate.images
Create a list of covariate images
simDSpat
Simulate a distance sample from a specified spatial point process
dspat
Fits spatial model to distance sampling data
weeds
Dubbo weed data
DSpat-package
Spatial modelling package for distance sampling data
simPts
Simulates point process on a rectangular grid
create.lines
Create a systematic sample of parallel lines across a grid
LTDataFrame
Creates covariate dataframes
create.points.by.offset
Create point dataframe offset from line
offset.points
Offset points from the line to actual position
project2line
Project points onto line
DSpat.covariates
Raster covariates study area
sample.points
Sample points within each transect and filter with specified detection function
transect.intensity
Compute expected and observed counts by distance within transect
DSpat.obs
Observation dataframe for DSpat
lines_to_strips
Convert lines to transects (strips)
dist2line
Compute perpendicular distances and projections onto line
lgcp.correction
Calculate Overdispersion factor for IPP fit via Monte Carlo Integration
DSpat.lines
Example DSpat lines dataframe
Internal
Internal DSpat functions