Simulated time series from 2 theta-logistic populations

Contains time series simulated from the discrete time theta-logisic model with noise: $$x_{t+1}=x_{t}e^{r(1-x_t^\theta)}e^{s\epsilon}$$ $$\epsilon \sim N(0,1)$$ PopA has \(\theta=3.5\) and PopB has \(\theta=2.5\). Both have \(r=1.2\) and \(s=0.05\) and time series length of 50, with random starting values and the first 200 iterates discarded.

thetalog2pop

Format

A data frame with 100 rows and 3 variables:

Time

Time index

Population

Population ID

Abundance

Abundance value

Source

The simulation code is in data-raw on the GPEDM Github page.