This study developed a new technique based on Probabilistic Distance Clustering (PDC) for evolving Awale player and to compare its performance with that of a technique based on approximation of minimum and maximum operators with generalized mean-value operator. The basic theory of pd-clustering is based on the assumption that the probability of an Euclidean point belonging to a cluster is inver...

We consider the analysis of clustered data using linear mixed effects models and generalized estimating equations, where covariates can be decomposed into betweenand within-cluster components. Under the false assumption of equal betweenand within-cluster covariate effects, we simultaneously study the asymptotic behavior of the estimators for regression coefficients, intra-cluster correlation an...

Abstract Finite mixtures of regressions with fixed covariates are a commonly used model-based clustering methodology to deal regression data. However, they assume assignment independence, i.e., the allocation data points clusters is made independently distribution covariates. To take into account latter aspect, finite random covariates, also known as cluster-weighted models (CWMs), have been pr...

Adomian decomposition method has been applied to solve many functional equations so far. In this article, we have used this method to solve the fuzzy differential equation under generalized differentiability. We interpret a fuzzy differential equation by using the strongly generalized differentiability. Also one concrete application for ordinary fuzzy differential equation with fuzzy input data...

Weighted likelihood, in which one solves Horvitz-Thompson or inverse probability weighted (IPW) versions of the likelihood equations, offers a simple and robust method for fitting models to two phase stratified samples. We consider semiparametric models for which solution of infinite dimensional estimating equations leads to √ N consistent and asymptotically Gaussian estimators of both Euclidea...

We introduce the so-called Clifford–Hermite polynomials in the framework of Dunkl operators, based on the theory of Clifford analysis. Several properties of these polynomials are obtained, such as a Rodrigues formula, a differential equation and an explicit relation connecting them with the generalized Laguerre polynomials. A link is established with the generalized Hermite polynomials related ...

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: AMS 2000 subject classification: 46N30 Keywords: B-spline Efficiency Empirical likelihood Generalized estimating equations G...

Methods of estimating the parameters generalized linear models for case paying insurance premiums to clients are considered. The iterative-recursive weighted least squares method, Adam optimization algorithm, and Monte Carlo method Markov chains were implemented. Insurance indicators target variable randomly generated due problem public access data. For latter, normal exponential law distributi...

We discuss in this paper the strong convergence for weighted sums of negatively orthant dependent (NOD) random variables by generalized Gaussian techniques. As a corollary, a Cesaro law of large numbers of i.i.d. random variables is extended in NOD setting by generalized Gaussian techniques.

We propose a new estimation method for multivariate failure time data using the quadratic inference function (QIF) approach. The proposed method efficiently incorporates within-cluster correlations. Therefore, it is more efficient than those that ignore within-cluster correlation. Furthermore, the proposed method is easy to implement. Unlike the weighted estimating equations in Cai and Prentice...