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...

Continuing increases in computing power and availability mean that many maximum likelihood estimation (MLE) problems previously thought intractable or too computationally difficult can now be tackled numerically. However, ML parameter estimation for distributions whose only analytical expression is as quantile functions has received little attention. Numerical MLE procedures for parameters of n...

In modeling the rate of return associated with financial instruments, common probability distributions include the lognormal, gamma, and Weibull distributions. Furthermore, the method of maximum likelihood is widely used to estimate the unknown parameters of distributions due to the highly desirable properties of maximum likelihood estimators (MLEs). These properties include asymptotic unbiased...

Patterns that resemble strongly skewed size distributions are frequently observed in ecology. A typical example represents tree size distributions of stem diameters. Empirical tests of ecological theories predicting their parameters have been conducted, but the results are difficult to interpret because the statistical methods that are applied to fit such decaying size distributions vary. In ad...

An exponentiated Pareto distribution is defined. We then consider maximum likelihood estimator (MLE) of the threshold parameter β with known parameters α and c for the exponentiated Pareto distribution in (2.1) and then obtain the MLE of the tail-probability of the exponentiated Pareto distribution. Finally, we consider MLE of reliability in two independent exponentiated Pareto distributions.

The Burr Type XII distribution is one of the systems of continuous distributions and is widely known because the distribution includes the characteristics of various well known distributions such as Weibull and gamma distributions. Maximum likelihood estimation (MLE) has been a common method in estimating model parameters. An alternative method that is the expectation-maximization (EM) algorith...

The maximum likelihood estimator MLE for the survival function ST under the proportional hazards model of censorship is derived and shown to di er from the Abdushukurov Cheng Lin estimator when the class of allowable distributions includes all continuous and discrete distributions The estimators are compared via an example The MLE is calculated using a Newton Raphson iterative procedure and imp...

Using probability plots and Maximum Likelihood Estimation (MLE), we fit lognormal distributions to data compiled by Ershow et al. for daily intake of total water and tap water by three groups of women (controls, pregnant, and lactating; all between 15-49 years of age) in the United States. We also develop bivariate lognormal distributions for the joint distribution of water ingestion and body w...

Estimating the unconstrained mean and covariance matrix is a popular topic in statistics. However, estimation of parameters Np(?,?) under joint constraints such as ?? = ? has not received much attention. It can be viewed multivariate counterpart classical problem N(????,????2) distribution. In addition to usual inference challenges non-linear among (curved exponential family), one deal with bas...

In simple random sampling, there is an equal chance of selection for each unit in the population. However, there are some practical situations where this might not be ideal. We consider the case of length-biased sampling, whereby the chance of selection of a unit is proportional to the length of the unit, by which the length-biased density is defined. Specifically we consider the case of a cont...