flimoptim_R {flimo}

Internal flimoptim function in R mode

Description

Computes several parameter inferences with R optimizer.

Usage

flimoptim_R(
  ndraw,
  data = NULL,
  dsumstats = NULL,
  simulatorQ = NULL,
  obj = NULL,
  nsim = 10,
  ninfer = 1,
  lower = 0,
  upper = 1,
  Theta0 = (lower + upper)/2,
  randomTheta0 = FALSE,
  obj_threshold = Inf,
  method = "L-BFGS-B",
  number_tries = 1,
  maxit = 1000,
  factr = 1e+07,
  pgtol = 0,
  show_trace = FALSE,
  store_quantiles = FALSE,
  par_names = NULL
)

Arguments

ndraw

Integer. Number of random variables to draw for one simulation of the model.

data

1D array containing the observations.

dsumstats

Summary statistics to measure distance between simulations and data. R function of type dsumstats(simulations, data) where simulations : 2D array and data : 1D array. ncol(simulations) = length(data) mandatory.

simulatorQ

Simulator of the stochastic process with fixed quantiles (see README). Theta is the parameter set for the simulations and quantiles are drawn in U(0,1).

obj

Objective function to minimize. Default : is directly computed from dsumstats and simulatorQ. R function of type objective(Theta, quantiles)

nsim

Integer. Number of simulations to run for each step of the optimization algorithm. Computation time grows linearly with this number. Default to 10.

ninfer

Integer. Number of independent inferences to run. Default to 1.

lower

1D array. Lower bounds for parameters. Same length as upper.

upper

1D array. Upper bounds for parameters. Same length as lower.

Theta0

1D array. Initial values of the parameters. Default : mean(lower, upper).

randomTheta0

Boolean. If True, Theta0 is randomly drawn between lower and upper bounds.

obj_threshold

Float. Threshold score. If Final value of objective is bigger, relaunch the inference if number_tries is not reached. The purpose is to avoid local minima. Default to Inf (no threshold).

method

String. Either "L-BFGS-B" (default) or any other method used by the base function optim. Stochastic methods do not work with flimo. If you want to provide bounds, you need to use L-BFGS-B or Brent.

number_tries

Integer. Number of tries (inferences) for the objective value to reach a point lower than obj_threshold. Default to 1.

maxit

Integer. Max number of iterations during optimization. Default to 1000.

factr

Float. Control parameter for L-BFGS-B method in stats::optim. Default to 1e7.

pgtol

Float. Control parameter for L-BFGS-B method in stats::optim. Default to 0.

show_trace

Boolean. If true, shows standard trace. Default to false.

store_quantiles

Boolean. If true, stores every quantiles used for inference, to reproduce the results.

par_names

vector of names for parameters. Default is "par1", ..., "parn".

Value

Object of class flimo_result (list) containing every information about convergence results.