Resampling: an improvement of Importance Sampling in varying population size models

Clicks: 153
ID: 271069
2016
Free PDF
Article Quality & Performance Metrics
Overall Quality Improving Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Request PDF | Resampling: an improvement of Importance Sampling in varying population size models | Sequential importance sampling algorithms have been defined to estimate likelihoods in models of ancestral population processes. However, these... | Find, read and cite all the research you need on ResearchGate
Reference Key
merle2016theoreticalresampling: Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Coralie Merle;Raphaël Leblois;François Rousset;Pierre Pudlo;
Journal theoretical population biology
Year 2016
DOI
http://dx.doi.org/10.1016/j.tpb.2016.09.002
URL
https://www.researchgate.net/publication/301838561_Resampling_an_improvement_of_Importance_Sampling_in_varying_population_size_models
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.