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popbio

popbio is an R package for modeling population growth rates using age- or stage-classified matrix models. The package consists mainly of methods described in Hal Caswell's Matrix Population Models (2001) and Morris and Doak's Quantitative Conservation Biology (2002). The R code was first submitted to CRAN in 2007.

See the wiki for more details.

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Version

Install

install.packages('popbio')

Monthly Downloads

2,335

Version

2.4.4

License

GPL-3

Maintainer

Chris Stubben

Last Published

May 3rd, 2018

Functions in popbio (2.4.4)

aq.census

Annual census data for Aquilegia in the southwestern US
Kendall

Find the best Kendall's estimates of mean and environmental variance for beta-binomial vital rates.
03.Morris

Converted Matlab functions from Morris and Doak (2002)
aq.matrix

Create a projection matrix for Aquilegia
fundamental.matrix

Fundamental matrix and age-specific survival
LTRE

Life Table Response Experiment
QPmat

Build a projection matrix from a time series of individuals (or densities) per stage.
generation.time

Generation time
aq.trans

Annual transition data for Aquilegia in the southwestern US
calathea

Projection matrices for a tropical understory herb
boot.transitions

Bootstrap observed census transitions
01.Introduction

Introduction to the popbio Package
betaval

Generate beta-distributed random numbers
hudsonia

Projection matrices for mountain golden heather
02.Caswell

Converted Matlab functions from Caswell (2001)
hudcorrs

Correlation matrices for Hudsonia vital rates
hudvrs

Best Kendall estimates of Hudsonia vital rate means and variances
hudmxdef

Matrix definition program for Hudsonia vital rates
eigen.analysis

Eigenvalue and eigenvector analysis of a projection matrix
matplot2

Plot a matrix
damping.ratio

Damping ratio
matrix2

Square matrices
net.reproductive.rate

Net reproductive rate
elasticity

Elasticity analysis of a projection matrix
colorguide

Plot a simple guide to colors
pfister.plot

Create log-log plots of variance vs. sensitivity and CV vs. elasticity
grizzly

Population sizes of grizzly bears in Yellowstone from 1959-1997
stoch.projection

Simulate stochastic growth from a sequence of matrices
head2

Return the first and last part of a matrix or dataframe
stoch.quasi.ext

Calculate quasi-extinction threshold
countCDFxt

Count-based extinction probabilities and bootstrap confidence intervals
teasel

Projection matrix for teasel
extCDF

Count-based extinction time cumulative distribution function
stage.vector.plot

Plot stage vector projections
stoch.growth.rate

Calculate log stochastic growth rate
test.census

Census data for hypothetical plant
image2

Display a matrix image
lambda

Population growth rate
logi.hist.plot

Plot logistic regression
lnorms

Generate random lognormal values for fertility rates
pop.projection

Calculate population growth rates by projection
projection.matrix

Construct projection matrix models using transition frequency tables
tortoise

Projection matrices for desert tortoise
multiresultm

Incorporate demographic stochasticity into population projections
nematode

Population densities for the sugarbeet cyst nematode
var2

Calculate a variance matrix
woodpecker

Survirvorship data for adult and juvenile Acorn Woodpeckers
splitA

Split a projection matrix into separate T and F matrices
stable.stage

Stable stage distribution
reproductive.value

Stable stage distribution
resample

Resample a projection matrix
vitalsim

Calculate stochastic growth rate and extinction time CDF using vital rates with within-year, auto-, and cross-correlations
stoch.sens

stoch.sens
whale

Projection matrix for killer whale
stretchbetaval

Generate stretched beta-distributed random numbers
mean.list

Calculate mean matrix
monkeyflower

Projection matrices for monkeyflower
sensitivity

Sensitivity analysis of a projection matrix
secder

secder
varEst

Estimate the variance of beta-binomial vital rates using approximation method of Akcakaya
vitalsens

Vital rate sensitivities and elasticities