dLogisticExponentialGrowth: Logistic-Exponential Growth Model

In nimbleCarbon: Bayesian Analyses of Radiocarbon Dates with NIMBLE

Logistic-Exponential Growth Model

Description

Density and random generation of a logistic-exponential growth model distribution.

Usage

dLogisticExponentialGrowth(x, a, b, r1, r2, k, mu, log)

rLogisticExponentialGrowth(n, a, b, r1, r2, k, mu)

Arguments

x	vector of calendar years (in BP).
a	lower (earliest) limit of the distribution (in BP).
b	upper (latest) limit of the distribution (in BP).
r1	growth rate of the logistic phase.
r2	growth rate of exponential phase.
k	initial proportion of the carrying capacity (must be between 0 and 1).
mu	change point (in BP).
log	TRUE or 1 to return log probability. FALSE or 0 to return probability.
n	number of random draws. Currently only n = 1 is supported, but the argument exists for standardization of "r" functions.

Value

For dLogisticExponentialGrowth: the probability (or likelihood) or log probability of an observed date x (in Cal BP). For rLogisticExponentialGrowth a simulated date in Cal BP.

Author(s)

Robert DiNapoli & Enrico Crema

Examples

p = list(r1=0.01,r2=-0.001,k=0.001,mu=4500)
modelPlot(model = dLogisticExponentialGrowth,a=6000,b=4000,params=p,alpha = 1)

nimbleCarbon documentation built on Aug. 14, 2023, 5:08 p.m.