flimoptim_R | R Documentation |

Computes several parameter inferences with R optimizer.

```
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
)
```

`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". |

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

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