نتایج جستجو برای: maximum likelihood estimation mle
تعداد نتایج: 596801 فیلتر نتایج به سال:
In this paper, we study the two-parameter maximum likelihood estimation (MLE) problem for the GE distribution with consideration of interval data. In the presence of interval data, the analytical forms for the restricted MLE of the parameters of GE distribution do not exist. Since interval data is kind of incomplete data, the EM algorithm can be applied to compute the MLEs of the parameters. Ho...
the performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. one of the most applicable traffic flow model in traffic control and management is lwr or metanet model. practically, key parameters in lwr model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...
The aim of this paper is to study the estimation of Pareto distribution on the basis of progressive type-II censored sample. First, the maximum likelihood estimator (MLE) is derived. Then the Bayes estimator of the unknown parameter of Pareto distribution is derived on the basis of Gamma prior distribution under entropy loss function. Further the empirical Bayes estimator also obtained by using...
This paper generalizes classical results on efficient point estimation in parametric models. The asymptotic optimality of maximum likelihood estimators is, generally, tied to both the regularity of the statistical model and symmetry of the loss function in the efficiency criterion. We examine the possibility of locally shifting or “bias-correcting” the MLE to achieve efficiency. In parametric m...
This paper takes issues with the appropriateness of applying the stochastic frontier analysis (SFA) technique to account for environmental effects and statistical noise in the popular three-stage data envelopment analysis (DEA). A correctly specified SFA model with a censored dependent variable and the associated maximum likelihood estimation (MLE) are proposed. The simulations show that the fi...
We study maximum likelihood estimation for the statistical model for both directed and undirected random graph models in which the degree sequences are minimal sufficient statistics. In the undirected case, the model is known as the beta model. We derive necessary and sufficient conditions for the existence of the MLE that are based on the polytope of degree sequences. We characterize in a comb...
abstract amusement programming, accomplishing ecological and/or environmental plans, in addition to establishing recreational centers, are of the important issues in regional and large-scale management of each country. herein, lack of financial resources to establish amusement areas, has led the natural resource management system to valuate such resources based upon new scientific methods. meas...
In this article, we consider the estimation of P[Y < X], when strength, X and stress, Y are two independent variables of Burr Type XII distribution. The MLE of the R based on one simple iterative procedure is obtained. Assuming that the common parameter is known, the maximum likelihood estimator, uniformly minimum variance unbiased estimator and Bayes estimator of P[Y < X] are discussed. The ex...
In this article, we propose generalized two-parameter (GTP) estimators and an algorithm for the estimation of shrinkage parameters to combat multicollinearity in multinomial logit regression model. addition, mean squared error properties are derived. A simulation study is conducted investigate performance proposed different sample sizes, degrees multicollinearity, number explanatory variables. ...
The satellite image deconvolution problem is ill-posed and must be regularized. Herein, we use an edge-preserving regularization model using a ' function, involving two hyperparameters. Our goal is to estimate the optimal parameters in order to automatically reconstruct images. We propose to use the Maximum Likelihood Estimator (MLE), applied to the observed image. We need sampling from prior a...
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