RiskMap (version 1.0.0)

set_control_sim: Set Control Parameters for Simulation

Description

This function sets control parameters for running simulations, particularly for MCMC methods. It allows users to specify the number of simulations, burn-in period, thinning interval, and various other parameters necessary for the simulation.

Usage

set_control_sim(
  n_sim = 12000,
  burnin = 2000,
  thin = 10,
  h = NULL,
  c1.h = 0.01,
  c2.h = 1e-04,
  linear_model = FALSE
)

Value

A list of control parameters for the simulation with class attribute "mcmc.RiskMap".

Arguments

n_sim

Integer. The total number of simulations to run. Default is 12000.

burnin

Integer. The number of initial simulations to discard (burn-in period, used for the MCMC algorithm). Default is 2000.

thin

Integer. The interval at which simulations are recorded (thinning interval, used for the MCMC algorithm). Default is 10.

h

Numeric. An optional parameter. Must be non-negative if specified.

c1.h

Numeric. A control parameter for the simulation. Must be positive. Default is 0.01.

c2.h

Numeric. Another control parameter for the simulation. Must be between 0 and 1. Default is 1e-04.

linear_model

Logical. If TRUE, the function sets up parameters for a linear model and only returns n_sim. Default is FALSE.

Author

Emanuele Giorgi

Claudio Fronterre

Details

The function validates the input parameters and ensures they are appropriate for the simulation that is used in the glgpm fitting function. For non-linear models, it checks that n_sim is greater than burnin, that thin is positive and a divisor of (n_sim - burnin), and that h, c1.h, and c2.h are within their respective valid ranges.

If linear_model is TRUE, only n_sim and linear_model are required, and the function returns a list containing these parameters.

If linear_model is FALSE, the function returns a list containing n_sim, burnin, thin, h, c1.h, c2.h, and linear_model.

See Also

Matrix, forceSymmetric

Examples

# Example with default parameters
control_params <- set_control_sim()

# Example with custom parameters
control_params <- set_control_sim(n_sim = 15000, burnin = 3000, thin = 20)