Using approximate Bayesian inference for a “steps and turns” continuous-time random walk observed at regular time intervals

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Introduction

Methods

Movement model with random time between movement decisions

Expression for the likelihood function

Inference using Approximate Bayesian Computation

  1. Compute a vector of summary statistics with observed data, S(y).

  2. Simulate parameters θ sampled from p(θ) and data y sampled from p(.∣θ).

  3. Compute a vector of summary statistics with simulated data, S(y).

  4. θ is accepted as a posterior sample, if ρ(S(y), S(y)) < δ, for some distance measure ρ and threshold δ.

  5. Repeat 2–4 K times.

Simulations

Assessment of the inference capacity of the ABC methods

Relative scale of observations and accuracy of the posterior density

Sheep data example

Results

Assessment of the inference capacity of the ABC methods

Relative scale of observations and accuracy of the posterior density

Sheep data

Discussion

Conclusions

Supplemental Information

Supporting Information

DOI: 10.7717/peerj.8452/supp-1

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Sofia Ruiz-Suarez conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Vianey Leos-Barajas and Juan Manuel Morales conceived and designed the experiments, authored or reviewed drafts of the paper, and approved the final draft.

Ignacio Alvarez-Castro conceived and designed the experiments, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The raw data is available at Figshare: Ruiz Suarez, Sofia; Morales, Juan Manuel (2019): GPS and DD sheep data. figshare. Dataset 10.6084/m9.figshare.9971642.v3.

R codes are available at Github: https://github.com/sofiar/ABC-steps-and-turns-.

Funding

This work was supported by CONICET by the project PICT 2015 0815. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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