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AHMbook (version 0.2.9)

Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology' Vols 1 and 2

Description

Provides functions to simulate data sets from hierarchical ecological models, including all the simulations described in the two volume publication 'Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS' by Marc Kéry and Andy Royle: volume 1 (2016, ISBN: 978-0-12-801378-6) and volume 2 (2021, ISBN: 978-0-12-809585-0), . It also has all the utility functions and data sets needed to replicate the analyses shown in the books.

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Version

Install

install.packages('AHMbook')

Monthly Downloads

446

Version

0.2.9

License

GPL (>= 3)

Maintainer

Ken Kellner

Last Published

August 23rd, 2023

Functions in AHMbook (0.2.9)

Count data from the Swiss Breeding Bird Survey MHB for crested tits from 1999 to 2015

Data from the Swiss Breeding Bird Survey for 6 species of tits

Time-to-detection data for peregrines from the French Jura mountains

simDynoccSpatialData

Simulated data from simDynoccSpatial for AHM2 section 9.6.1.2 (page 564)

greenWoodpecker

Count data from the Swiss Breeding Bird Survey for Green Woodpeckers from 2004 to 2017

Data for Dutch wagtails

SwissMarbledWhite

Data for Swiss Marbled White butterflies

American Tree Sparrow data from Alaska

Territory-level, multi-state detection/nondetection data for Eagle Owls in Switzerland

Point count and spot-mapping data for Chestnut-sided Warbler

spottedWoodpecker

Data for observations of Middle Spotted Woodpecker in Switzerland

Plot the results for a Gaussian state-space model

Helper function to draw scale for image

Mapping of residuals

Model selection results from a list of 'unmarkedFitOccuFP' models

Compute results of a Joint Species Distribution Model (JSDM)

Functions to return fit statistics

Data for the Mighty Water Voles of Scotland, UK.

Compute multinomial cell probabilities

Coordinates for a wiggly line transect

Simulate community occupancy or community abundance data

Calculates the pair-wise distances between two sets of points

Constant effort site (CES) data for British Willow Warblers

Fictional data for dragonflies

Data for UK Marbled White butterflies

duskySalamanders

Age-classified counts of dusky salamanders from two mid-Atlantic states in the USA

Simulate detection/nondetection data under a general dynamic community (site-occupancy) model

Simulate count data under the dynamic N-mixture model of Dail-Madsen

Simulate detection/nondetection data for static 3-level occupancy models

Simulate individual capture-histories under a Cormack-Jolly-Seber (CJS) survival model

Produce some residual plots

Function to play Royle-Nichols (RN) model

Simulate line transect data for density surface modeling

Plot results from posterior predictive check

Simulate count data under a binomial N-mixture model

Simulate data for an integrated species distribution model (SDM) of Dorazio-Koshkina

Simulate data under HDS protocol with groups

Create a Gaussian random field with negative exponential correlation

Simulate a Poisson point process

Simulate data under hierarchical distance sampling protocol (line or point)

simDynoccSpatial

Simulate data under a dynamic occupancy model with spatial autocorrelation

Simulate detection data for diseased frogs

Simulate open hierarchical distance sampling data

Simulate data under a demographic dynamic occupancy model

Simulate detection/nondetection data under a wide variety of non-spatial dynamic occupancy models

Simulate data under hierarchical distance sampling point transect protocol

Simulate open distance sampling data for the Island Scrub Jays

Simulate replicated detection/nondetection data under a spatial, static occupancy model

Simulate replicated counts under a spatial, static binomial N-mixture model

Simulate HDS time-removal or double-observer data

Simulate data for static occupancy models under wide range of conditions

Simulate data for an integrated distance sampling, point count and occupancy study

Simulation of distance sampling data.

Generate counts from a single population observed over T years under a binomial observation process

Simulate data for binomial and multinomial mixture models

Simulate the multinomial-mixture model

Generate counts under a variant of a 'phenomenological model'

Simulate time-to-detection occupancy data (single visits)

simSpatialDSline

Simulate data for a standardized line transect

Simulate data for replicate line transect surveys with temporary emigration

Scaling and centering of vectors, matrices and arrays

Validates simulated observational data against data-generating values.

Simulates data for a basic spatial distance sampling model

Simulate non-hierarchical point transect (= point count) data

Simulate N-mixture data under a time-for-space substitution design

Simulate a spatial point pattern in a heterogeneous landscape

Simulate data for a demographic state-space model

Prepare input for BUGS model when fitting a spline for a covariate

Simulate static occupancy data

Simulates data for a hierarchical spatial distance sampling model

Starting values for survival analysis in JAGS/BUGS

BerneseOberland

Landscape data for the Bernese Oberland around Interlaken, in the Alps of central Switzerland

Converts capture-histories to an m-array

Cross correlations for MCMC output

Data for Eurasian lynx from Switzerland and Italy (only Alps).

AHMbook-package

Functions and data for the Book “Applied Hierarchical Modeling in Ecology” Volumes 1 and 2

Data from the Swiss Breeding Bird Survey MHB 2014

Data for Red Squirrels in Switzerland from the Swiss breeding bird survey MHB

Data from surveys of birds in Finnmark in NE Norway

FrenchPeregrines

Data for observations of peregrines from the French Jura mountains

Camera trap data for Bobcat, Coyote and Red Fox

Warbler point count data from the Hubbard Brook Experimental Forest

Data for 1ha quadrats from the Swiss Breeding Bird Atlas

Data from the Swiss Breeding Bird Survey MHB for European Crossbill from 2001 to 2012