The idea of using kernel functions combined with distributions to propose new has recently been used suggest continuous distributions. This article the Epanechnikov function Weibull distribution produce Epanechnikov-Weibull (EWD). We have presented some properties EWD, like moments, MLEs, reliability analysis functions, Rényi entropy and quantile function. estimated model parameters maximum lik...

Delft University of Technology and Vrije Universiteit Amsterdam, University of Washington and University of Washington We study nonparametric estimation for current status data with competing risks. Our main interest is in the nonparametric maximum likelihood estimator (MLE), and for comparison we also consider the ‘naive estimator’ of Jewell, Van der Laan and Henneman [10]. Groeneboom, Maathui...

Aims. Deriving accurate frequencies, amplitudes, and mode lifetimes from stochastically driven pulsation is challenging, more so, if one demands that realistic error estimates be given for all model fitting parameters. As has been shown by other authors, the traditional method of fitting Lorentzian profiles to the power spectrum of time-resolved photometric or spectroscopic data via the Maximum...

Estimating parameters in a mixture of normal distributions dates back to the 19th century when Pearson originally considered data of crabs from the Bay of Naples. Since then, many real world applications of mixtures have led to various proposed methods for studying similar problems. Among them, maximum likelihood estimation (MLE) and the continuous empirical characteristic function (CECF) metho...

Tsallis et al. proposed these distributions to handle statistical-mechanical systems with long-range interactions, necessitating (it is claimed) a non-extensive generalization of the ordinary Gibbs-Shannon entropy. Following Jaynes’s procedure of maximizing an entropy subject to constraints on expectation values [2], they got the q-exponential distributions, in which κ enforces the constraints,...

Abstract The Pareto/NBD model is one of the best-known models in customer base analysis. Extant literature has brought up three different Markov Chain Monte Carlo (MCMC) procedures for parameter estimation this model. Nevertheless, main research gaps remain. Firstly, issue hyper sensitivity these been disregarded even though crucial when dealing with small sample sizes. Secondly, present lacks ...

Rotating machinery is the most common machinery in industry. The root of the faults in rotating machinery is often faulty rolling element bearings. This paper presents a technique using optimized artificial neural network by the Bees Algorithm for automated diagnosis of localized faults in rolling element bearings. The inputs of this technique are a number of features (maximum likelihood estima...

The paper focuses on the asymptotic comparison of maximum likelihood estimators and uniformly minimum variance unbiased (with respect to quadratic loss) for one-parameter truncation families where a sufficient statistic is either or sample. Easily verifiable conditions are formulated under which those results valid.

Two related methods exist for sampling from posterior distributions of the MLE with a known prior Newton & Raftery (1994) [8], Efron (2011) [4]. We compare them by examining asymptotic Edgeworth expansions of their pivotal distributions. The result is that Newton & Raftery (1994) is 2nd order consistent to the posterior distribution with prior proportional to the Fisher Information, under some ...

Probabilistic human health exposure assessment is commonly challenged by non-detected data in measurement datasets and dependencies among sampling distributions. Methods for dealing with nondetected data, dependencies and associated uncertainty are introduced. An example case study was performed to demonstrate application of the methods and investigate how exposure estimates and associated unce...