fit.prob.travel: Estimate probability of travelling outside origin

In gilesjohnr/hmob: Tools for analyzing human mobility data

Description

This function fits a hierarchical model that estimates the probability an individual travels outside their home location within the time period of the survey (tau). The model estimates both the overall population-level probability of travel (tau_pop) and the origin-level probability of travel (tau_i). Further this method is designed for sparse observations that typically result from travel survey data, where unobserved routes of travel regress to the population mean.

Usage

fit.prob.travel(
  V.travel,
  V.tot,
  n.chain = 4,
  n.burn = 1000,
  n.samp = 1000,
  n.thin = 1,
  DIC = FALSE,
  parallel = FALSE
)

Arguments

V.travel	named vector of total number of people that reported travelling outside their home location
V.tot	named vector of the total number of individuals in travel survey for each location
n.chain	number of MCMC sampling chains
n.burn	number of iterations to discard before sampling of chains begins (burn in)
n.samp	number of iterations to sample each chain
n.thin	interval to thin samples
DIC	logical indicating whether or not to calculate the Deviance Information Criterion (DIC)
parallel	logical indicating whether or not to run MCMC chains in parallel or sequentially (default = FALSE)
n.adapt	number of adaptive iterations

Value

dataframe giving input data along with estimates of travel probability for each location

Author(s)

John Giles

See Also

Other model: fit.gravity(), fit.jags(), rjags.combine(), rjags.mcmc.list(), summarize.hmob()

Other gravity: fit.gravity(), sim.gravity.duration(), sim.gravity()

gilesjohnr/hmob documentation built on Aug. 8, 2020, 1:26 a.m.