The Erlang-Truncated Exponential ETE distribution is modified and the new lifetime distribution is called the Extended Erlang-Truncated Exponential EETE distribution. Some statistical and reliability properties of the new distribution are given and the method of maximum likelihood estimate was proposed for estimating the model parameters. The usefulness and flexibility of the EETE distribution ...

In Minimum Message Length (MML) clustering (unsupervised classification, mixture modelling) the aim is to infer a set of classes that best explains the observed data items. There are cases where parts of the observed data do not need to be explained by the inferred classes but can be used to improve the inference and resulting predictions. Our main contribution is to provide a simple and flexib...

This paper examines two asymmetric stochastic volatility models used to describe the heavy tails and volatility dependencies found in most financial returns. The first is the autoregressive stochastic volatility model with Student’s t-distribution (ARSV-t), and the second is the multifactor stochastic volatility (MFSV) model. In order to estimate these models, the analysis employs the Monte Car...

In recent years, a persuasive argument has been made for the use of information criterion (IC) model selection in place of null hypothesis significance testing (NHST) based on P values (Johnson 1999, Burnham and Anderson 2002, Johnson and Omland 2004). In this issue, Murtaugh (2014) questions the basis for this argument. We comment on this paper from the perspective of early-career ecologists a...

Methodologists have criticized the use of significance tests in the behavioral sciences but have failed to provide alternative data analysis strategies that appeal to applied researchers. For purposes of comparing alternate models for data, information-theoretic measures such as Akaike AIC have advantages in comparison with significance tests. Model-selection procedures based on a min(AIC) stra...

Generalized and subset generalized bilinear models which are capable of achieving stationary for all non-linear series were developed to accommodate error process of elements of 2q-1 possible subsets with a view to achieve better model in the generalized bilinear model. The parameters of the models are estimated using robust nonlinear least-square method and Newton-Raphson iterative method. An ...

A statistical model of gear mesh vibration signals is proposed in this paper. It is seen that the sample mean is first removed from the gear mesh vibration signal, and the remaining signal components are approximated with a set of sinusoidal functions in the signal model. The signal model parameters can be estimated by the least-square method and the optimal model order is determined based on t...

We propose a method of analyzing collections of related curves in which the individual curves are modeled as spline functions with random coefficients. The method is applicable when the individual curves are sampled at variable and irregularly spaced points. This produces a low-rank, low-frequency approximation to the covariance structure, which can be estimated naturally by the EM algorithm. S...

Cytogenetic abnormalities are important diagnostic and prognostic criteria for acute myeloid leukemia (AML). A flow cytometry-based imaging approach for FISH in suspension (FISH-IS) was established that enables the automated analysis of several log-magnitude higher number of cells compared to the microscopy-based approaches. The rotational positioning can occur leading to discordance between sp...

It is a relatively well-known fact that in problems of Bayesian model selection, improper priors should, in general, be avoided. In this paper we will derive and discuss a collection of four proper uniform priors which lie on an ascending scale of informativeness. It will turn out that these priors lead us to evidences that are closely associated with the implied evidence of the Bayesian Inform...