Daphnia-tutorial

PanelPOMP data analysis in R: A four-species ecological system

Status: complete. The rendered tutorial is daphnia_tut_R.html. The source is daphnia_tut_R.qmd; Makefile renders it and data/ holds the Excel data and the two CSV extracts it reads.

Prerequisites

Before starting the R version of this tutorial, ensure you have the following R packages installed:

install.packages(c("pomp", "panelPomp", "tidyverse"))

Tutorial Contents

1. PanelPOMP Model Setup: How to specify a mechanistic model with shared and unit-specific parameters
2. Panel Iterated Filtering: Implementation of the PIF algorithm for likelihood maximization
3. Parameter Estimation: Strategies for multi-stage optimization with tempering
4. Profile Likelihood: Computing confidence intervals using the MCAP algorithm
5. Model Diagnostics: Simulation studies and residual analysis

Note: Some computationally intensive examples may require adjustment of run_level parameters:

• Level 1: Quick debugging (~minutes)
• Level 2: Local computation (~1 hour on 36 cores)
• Level 3: Full estimation (~40 hours on 36 cores)

The R and Python tutorials use independent run-level definitions; these levels do not correspond to the Python ones.