PoPS 2.0.1

Added

• calibrate can now use the Mathews Correlation Coefficient as the summary statistic of
  to keep or reject parameter sets (@ChrisJones687, #145).

• validate, calibrate, pops_multirun, and pops now take use_survival_rates, survival_rate_month,
  survival_rate_day, and survival_rates_file (@ChrisJones687, #147).

• validate, calibrate, pops_multirun, and pops now take network_movement as a parameter. This
  parameter controls how dispersal occurs along the network (@ChrisJones687, #147).

Changed

• validate, calibrate, pops_multirun, auto_manage and pops no longer take
  network_min_distance and network_max_distance as these parameters are now passed
  in through the parameter_means and parameter_cov_matrix parameters and are calibrated
  as part of the calibration if network kernel is selected (@ChrisJones687, #140).

• calibrate now calibrates the network_min_distance and network_max_distance parameters
  during calibration and they are now part of the parameter_means and parameter_cov_matrix
  that are exported from the calibration (@ChrisJones687, #140).

• calibrate has more flexible success metric options removes use_distance, use_rmse, and use_mcc
  parameters and replaces it with the more flexible success_metrics parameter. Users can now
  select multiple combinations of different success metrics for the calibration
  (@ChrisJones687, #150).

• pops_multirun removed the ability to write all simulations. (@ChrisJones687, #144).

• the deterministic parameter has been renamed to dispersal_stochasticity. This
  was done to be more consistent with generate_stochasticity, movement_stochasticity, and
  establishment_stochasticity parameters (@ChrisJones687, #147).

• validate, calibrate, pops_multirun, and pops now propogate uncertainty from host and
  initial conditions. This adds the parameters use_initial_condition_uncertainty and
  use_host_uncertainty. If use_initial_condition_uncertainty is TRUE the infected_file and/or
  exposed_file need to have 2 layers a mean and standard deviation. If use_host_uncertainty is
  is TRUE the host_file needs to have 2 layers a mean and standard deviation. For each model run
  a host and/or initial conditions are drawn from the mean and sd layers so that each run has a
  unique host and/or initial conditions this will allow for both propogation of uncertainty from
  these sources but also partitioning (@ChrisJones687, #151).

Fixed

• fixed error on parameter draws in select situations (@ChrisJones687, #146).