run_sim1_univariate: A Function to fit univariate ABM for simulation 1

In andyhoegh/moveR: Agent-Based Models for Animal Movement

Description

A Function to fit univariate ABM for simulation 1

Usage

run_sim1_univariate(num_mcmc, num_particles, data, m_mu, sigmasq_m, nu,
  sigmasq0, nu_eps, sigmasq0_eps, mu_theta_mean, var_theta)

Arguments

num_mcmc	The number of MCMC iterations
num_particles	The number of particles to use in particle filter
data	Time_points x 2 matrix of observed locations
m_mu	Prior values for step size mean: # mu ~ N(m_mu, sigmasq_m)
sigmasq_m	Prior values for step size mean: # mu ~ N(m_mu, sigmasq_m)
nu	Prior values for step size standard deviation: sigmasq_u ~ IG(nu/2,sigmasq0 * nu / 2)
sigmasq0	Prior values for step size standard deviation: sigmasq_u ~ IG(nu/2,sigmasq0 * nu / 2)
nu_eps	Prior values for observation error: # sigmasq_eps ~ IG(nu_eps/2,nu_eps * sigmasq0_eps / 2)
sigmasq0_eps	Prior values for observation error: # sigmasq_eps ~ IG(nu_eps/2,nu_eps * sigmasq0_eps / 2)
mu_theta_mean	Prior values for projected normal: mu_theta ~ N(mu_theta_mean, var_theta)
var_theta	Prior values for projected normal: mu_theta ~ N(mu_theta_mean, var_theta)

Value

A list containing the path and the log probability of the path

andyhoegh/moveR documentation built on Feb. 8, 2020, 11:20 p.m.