Examples of using Parameter estimation in English and their translations into Ukrainian
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Parameter estimation of the hidden Gibbs…".
R package Several ABC algorithms for performing parameter estimation and model selection.
М27 Parameter estimation of harmonic signal in terms of interference.
The formal device forDelphi process efficiency modeling of scalar parameter estimation was developed.
Latyuk Parameter estimation of the hidden Gibbs field using Gibbs samplers.
Various extensions to the DBSCAN algorithm have been proposed, including methods for parallelization, parameter estimation, and support for uncertain data.
M27 Parameter estimation of harmonic signal in terms of interference(Number of comments: 0).
Additionally, Advanced Virgo, KAGRA, and a possible third LIGO detector in India will extend the network andsignificantly improve the position reconstruction and parameter estimation of sources.[1].
Outside of parameter estimation, the ABC framework can be used to compute the posterior probabilities of different candidate models.
A stochastic volatility model structure is proposed for multidimensional case andthe methodology is considered for its parameter estimation with the use of Markov chain Monte Carlo technique.
PEST is a package designed for parameter estimation and uncertainty analysis in computer models, allowing model calibration.
His work in mathematical statistics was devoted mostly to the applications of information theory,including asymptotically sufficient statistics for parameter estimation and nonparametric estimation.
In the case of parameter estimation in partially observed systems, the profile likelihood can be also used for identifiability analysis.
Unlike GPD, exGPD has moments of all orders regardless of its parameter conditions and possesses separate interpretations for the scale parameter and shape parameter, which makes parameter estimation more efficient.
Since parameter estimation is based on the minimization of squared error, a few extreme observations can exert a disproportionate influence on parameter estimates.
Both methods make use of two-part codes: the first part always represents the information that one is trying to learn, such as the index of a model class(model selection)or parameter values(parameter estimation); the second part is an encoding of the data given the information in the first part.
Sequential procedures of statistical parameter estimation application in engineering practice for the example of air navigation devices extending the term of service(resource) are considered.
In parameter estimation problems, the use of an uninformative prior typically yields results which are not too different from conventional statistical analysis, as the likelihood function often yields more information than the uninformative prior.
Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data.
In statistics, typically a loss function is used for parameter estimation, and the event in question is some function of the difference between estimated and true values for an instance of data.
For example, the introduction of deterministic global parameter estimation led to reports that the global optima obtained in several previous studies of low-dimensional problems were incorrect.
Norbert Fuhr introduced the general idea of MLR in 1992,describing learning approaches in information retrieval as a generalization of parameter estimation;[27] a specific variant of this approach(using polynomial regression) had been published by him three years earlier.[2] Bill Cooper proposed logistic regression for the same purpose in 1992[3] and used it with his Berkeley research group to train a successful ranking function for TREC.
ISP NPP researchers use these indicators for development a parameters estimation method of radionuclide migration by groundwaters and recommendations about minimization of negative impact of radioactive contamination on the environment.
Multi- frequency and multi-angle radar methods application peculiarities for parameters estimation of oil pollutions on sea surface.
With the aim to determine the most exact techniques of these parameters estimation general methods have been validated.
A technology of the regress equation parameters estimation where initial data represents indistinct numbers with known accessory functions is considered.
Recurrent modifications of Gauss and Gram-Schmidt methods for solving of the linear equations systems are for the first time developed.The modifications allow to considerably decreasing the computation time for parameters estimation stage in case of successive complication of models structures.
There is no estimation for this parameter, but the distance functions needs to be chosen appropriately for the data set.
Because of the parameter identification problem,ordinary least squares estimation of the structural VAR would yield inconsistent parameter estimates.
In many cases,the likelihood is a function of more than one parameter but interest focuses on the estimation of only one, or at most a few of them, with the others being considered as nuisance parameters.