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DSpat (version 0.1.0)
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
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0.1.0
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Install
install.packages('DSpat')
Monthly Downloads
40
Version
0.1.0
License
GPL (>= 2)
Maintainer
Jeff Laake
Last Published
May 6th, 2009
Functions in DSpat (0.1.0)
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Internal
Internal DSpat functions
LTDataFrame
Creates covariate dataframes
DSpat.lines
Example DSpat lines dataframe
integrate.intensity
Integrated intensity of fitted model
simCovariates
Simulates covariates for an example in DSpat
create.covariate.images
Create a list of covariate images
weeds.covariates
Covariate grid for Dubbo weed data
lgcp.correction
Calculate Overdispersion factor for IPP fit via Monte Carlo Integration
create.lines
Create a systematic sample of parallel lines across a grid
quadscheme.lt
Create line transect quadrature for spatstat
project2line
Project points onto line
lines_to_strips
Convert lines to transects (strips)
DSpat.obs
Observation dataframe for DSpat
weeds.all
Dubbo weed data with constructed y-coordinate
dist2line
Compute perpendicular distances and projections onto line
offset.points
Offset points from the line to actual position
DSpat.covariates
Raster covariates study area
weeds.lines
Transect lines from Dubbo weed data
dspat
Fits spatial model to distance sampling data
sample.points
Sample points within each transect and filter with specified detection function
create.points.by.offset
Create point dataframe offset from line
weeds.obs
Observations from Dubbo weed data
simPts
Simulates point process on a rectangular grid
simDSpat
Simulate a distance sample from a specified spatial point process
DSpat-package
Spatial modelling package for distance sampling data
transect.intensity
Compute expected and observed counts by distance within transect
weeds
Dubbo weed data