ASMbook (version 1.0.2)

simDat20: Simulate data for Chapter 20: Integrated model

Description

Simulate three count datasets under different data collection conditions

Usage

simDat20(
  nsites1 = 500,
  nsites2 = 1000,
  nsites3 = 2000,
  mean.lam = 2,
  beta = -2
)

Value

A list of simulated data and parameters.

nsites1

Number of sites in regular count dataset

nsites2

Number of sites in zero-truncated count dataset

nsites3

Number of sites in detection/non-detection dataset

mean.lam

Mean site abundance

beta

Slope for elevation covariate

C1

Simulated regular counts from dataset 1

C2

Simulated regular counts from dataset 2

C3

Simulated regular counts from dataset 3

ztC2

Simulated zero-truncated counts from dataset 2

y

Simulated detection/non-detection data from dataset 3

Arguments

nsites1

Number of sites in regular count dataset

nsites2

Number of sites in zero-truncated count dataset

nsites3

Number of sites in detection/non-detection dataset

mean.lam

Mean site abundance

beta

Slope for elevation covariate

Author

Marc Kéry

Examples

str(dat <- simDat20())             # Implicit default arguments

# Revert to an 'integrated Poisson/binomial model-of-the-mean': no effect of elevation on abundance
str(dat <- simDat20(nsites1 = 500, nsites2 = 1000, nsites3 = 2000, mean.lam = 2, beta = 0))