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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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Version

Install

install.packages('DSpat')

Monthly Downloads

6

Version

0.1.5

License

GPL (>= 2)

Maintainer

Jeff Laake

Last Published

November 7th, 2012

Functions in DSpat (0.1.5)

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