# sequential_design_for_predator_prey_experiments
This repository contains both R and MATLAB code that conducts optimal sequential experimental design for predator-prey experiments. The code is associated with the following paper: https://royalsocietypublishing.org/doi/10.1098/rsif.2020.0156. This code considers optimal designs for the purpose of precise parameter estimation and/or model discrimination. However, the user is free to define their own experimental goal. The code is commented and a brief description of how to use the code is included.
食饵捕食模型matlab代码-sequential_design_for_predator_prey_experiments:该...
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2021-05-26
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sequential_design_for_predator_prey_experiments-master.zip （39个子文件） 
sequential_design_for_predator_prey_experiments-master R code 
parameter_estimation_utility.R 2KB generate_data.R 3KB utility_plot.R 1KB model_discrimination_utility.R 2KB move_step.R 3KB resample_then_move.R 1KB SMC_plot.R 2KB
hassell_data.txt 560B additional_functions.R 12KB prior_sampling.R 1KB total_entropy_utility.R 3KB SMC_algorithm.R 8KB papanikolau_data.txt 388B R code instructions.txt 265B README.md 554B MATLAB code total_entropy_utility.m 2KB parameter_estimation_utility.m 2KB move_step.m 2KB multinomial_resampling.m 399B logsumexp.m 356B plot_data.m 830B log_betabinpdf.m 591B log_binpdf.m 297B ode_M2.m 229B find_parameters.m 548B log_prior.m 780B generate_data.m 806B log_lik.m 380B ode_M3.m 240B hassell_data.mat 328B SMC.m 7KB residual_resampling.m 474B log_likelihood.m 1KB ode_solver.m 966B papanikolau_data.mat 239B prior_sampling.m 771B plotSMC.m 980B model_discrimination_utility.m 2KB
MATLAB code instructions.docx 20KB资源评论
