fit.optimization: fit.optimization

In khaors/pumpingtest: R Package for the analysis and evaluation of pumping tests

Description

Function to estimate the aquifer parameters from a pumping test using several optimization functions.

Usage

fit.optimization(ptest, model, obj.fn = "rss", opt.method = "nls",
  lower = 1e-09, upper = Inf, control.par, seed = 12345)

Arguments

ptest	A pumping_test object.
model	A character string specifying the model used in the parameter estimation.
obj.fn	A character string specifying the objective function used in the parameter estimation. Currently the following objective functions are included: 'rss': Residual sum of squares 'mnad': Mean absolute deviation 'mxad': Maximum absolute deviation 'loglik': Loglikelihood function
opt.method	A character string specifying the optimization method used in the parameter estimation. Currently the following methologies are included: 'nls': Nonlinear regression 'sa': Simulated Annealing (GenSA package) 'ga': Genetic Algorithms (GA package) 'l-bfgs-b': using optim function (stats package) 'pso': Particle Swarm Optimization (pso package) 'copulaedas': Estimation of Distribution Algorithms Based on Copulas (copulaedas package) 'de': Differential Evolution (DEoptim package)
lower	A numeric vector with the lower values of the search region
upper	A numeric vector with the upper values of the search region
control.par	A list with the parameters of the optimization method
seed	A random seed

Value

A list with the following entries:

• hydraulic_parameters: hydraulic parameters of the model (includes transmissivity, storage coefficient and radius of influence, or others)

• parameters: fitted parameters (including a and t0 and other depending on the model)

• resfit: The list or object returned by the optimization driver of each method.

• value: The value of the objective function reached at the end of the optimization run.

Author(s)

Oscar Garcia-Cabrejo [e-mail]

See Also

Other base functions: additional.parameters<-, confint.pumping_test, confint_bootstrap, confint_jackniffe, confint_wald, estimated<-, evaluate, fit.parameters<-, fit.sampling, fit, hydraulic.parameter.names<-, hydraulic.parameters<-, model.parameters, model<-, plot.pumping_test, plot_model_diagnostic, plot_sample_influence, plot_uncert, print.pumping_test, pumping_test, simulate, summary.pumping_test

Examples

## Not run: 
# Define pumping_test object
data("boulton")
ptest.boulton <- pumping_test("Well1", Q = 0.03, r = 20,
                              t = boulton$t, s = boulton$s)
# Parameter estimation using L-BFGS-B
ptest.boulton.bfgs.rss <- fit.optimization(ptest.boulton,
"boulton", obj.fn = "rss", opt.method = "l-bfgs-b",
seed = 54321)
# Parameter estimation using Simulated Annealing
ptest.boulton.sa.rss <- fit.optimization(ptest.boulton,
"boulton", obj.fn = "rss", opt.method = "sa", seed = 54321)
# Parameter estimation using Genetic Algorithms
ptest.boulton.ga.rss <- fit.optimization(ptest.boulton,
"boulton", obj.fn = "rss", opt.method = "ga", seed = 54321)
# Parameter estimation using Differential Evolution
ptest.boulton.de.rss <- fit.optimization(ptest.boulton,
                        "boulton", obj.fn = "rss", opt.method = "de", seed = 54321)
# Parameter estimation using Particle Swarm Optimization
ptest.boulton.pso.rss <- fit.optimization(ptest.boulton,
                         "boulton", obj.fn = "rss", opt.method = "pso", seed = 54321)

## End(Not run)

khaors/pumpingtest documentation built on Nov. 15, 2019, 8:10 p.m.