Journal of Mathematics and Statistics

Special Issue on Distribution Theory, Estimation and Inference


Description

Journal of Mathematics and Statistics is currently welcoming submissions for a Special Issue on Distribution Theory, Estimation and Inference.

In connection with ICoMS2019 Conference to be held in July 2019, this special issue invites extended contributions from participants to be considered for peer review in the Journal of Mathematics and Statistics.

Aims and Scope

This special Issue will focus on all aspects of Distribution Theory, Estimation and Inference. Topics of current interest include, but are not limited to the following:

  1. Regression Modelling
  2. Multivariate data analysis
  3. Time Series Models
  4. Generalized linear models
  5. Simulation
  6. Resampling
  7. Estimation
  8. Prediction and testing in linear models
  9. Robustness of relevant statistical methods
  10. Generalizations to nonlinear models
  11. Multivariate Analysis
  12. Order Statistics
  13. Extreme Value Theory

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts will be thoroughly refereed through a peer-review process.

Editorial Information

Principal Guest Editor:

Carlos A. Coelho
Department of Mathematics and Center of Mathematics and its Applications,
Faculty of Sciences and Technology, New University of Lisbon, Portugal

Carlos A. Coelho is Full Professor of Statistics at the Mathematics Department of Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa, Portugal, and nominated Chair of Research in Computational and Methodological Statistics at the Department of Statistics of the University of Pretoria, South-Africa. He holds a Ph.D. in Biostatistics from the University of Michigan, Ann Arbor, MI, U.S.A., and his main areas of research are Mathematical Statistics and Distribution Theory, namely the study and development of exact and near-exact distributions for likelihood ratio test statistics used in Multivariate Analysis. Other areas of interest are Estimation, Univariate and Multivariate Linear, Generalized Linear and Mixed Models, as well as Computational Statistics. In a 2004 paper published in the Journal of Multivariate Analysis, he laid the foundations for what he called 'near-exact distributions'. Since then these have been successfully applied to a large number of statistics, with more than 40 papers published on this topic. The technique combines an adequately developed decomposition of the characteristic function of the statistic or random variable being studied or of its logarithm, decomposition which often is an adequate factorization, with the procedure of keeping the most of this characteristic function unchanged and replacing the remaining part by an adequate asymptotic approximation. All this is done in order to obtain a manageable and very well-fitting approximation, which may be used to compute very sharp p-values and quantiles. Carlos A. Coelho is an Elected Member of the International Statistical Institute and is co-editor of the new Springer Book Series in "Emerging Topics in Statistics and Biostatistics". He also serves as Associate Editor in the Editorial Boards of Journal of Applied Statistics, REVSTAT, Journal of Statistical Theory and Practice, Journal of Interdisciplinary Mathematics, American Journal of Mathematical and Management Sciences and Discussiones Mathematicae-Probability and Statistics.

Guest Editors:

Dário Ferreira
Department of Mathematics and Center of Mathematics and Applications,
Avenida Marquês D'Ávila e Bolama, University of Beira Interior, Covilhã, Portugal

Dário Ferreira is Assistant Professor at the Mathematics Department of the University of Beira Interior (Covilhã, Portugal), member of the Center of Mathematics at the same University and an active member of the Portuguese Society of Statistics (SPE). He has graduated in Mathematics at the University of Évora and received his Ph.D. in Mathematics/Statistics from the University of Beira Interior. His general research area is in Linear Models. More specifically, He works in the estimation of variance components using algebraic and stochastic methods. He has been publishing research in this field and has been guest to participate in some research projects, co-chaired several international conferences and workshops, being also a program committee member of several international conferences.

Sandra S. Ferreira
Department of Mathematics and Center of Mathematics and Applications,
Avenida Marquês D'Ávila e Bolama, University of Beira Interior, Covilhã, Portugal

Sandra S. Ferreira is Assistant Professor at the University of Beira Interior (UE), Portugal. Her publications and current research interests focus on statistical inference for estimable functions and variance components, in linear mixed models with commutative orthogonal block structure (COBS). She completed her Ph.D. in 2006 at the University of Beira Interior, where she teaches courses in basic statistics, quantitative methods, hierarchical linear models and multivariate analysis. She is member of the working group (WG) CMStatistics (this WG focuses on all computational and methodological aspects of statistics) and member of IEOM Society and serves as an editorial board member of several journals.

João T. Mexia
Center of Mathematics and its Applications,
Faculty of Sciences and Technology, New University of Lisbon, Portugal

João Tiago Praça Nunes Mexia was born in Lisbon in June of 1939. The most part of his career was as Full Professor at the FCT/UNL-Faculty for Sciences and Technology of the New University of Lisbon. At that time he supervised the teaching of Statistics at FCT/UNL and directed the Research Center in Mathematics of the University (CMA-Center for Mathematics and its Applications) from 1999 to 2009. In 2009 he became Emeritus Professor. Until now he supervised 19 Ph.D. and co-supervised 12 Ph.D. His research is centered on Linear Statistical Inference, having almost 100 papers published in International Journals.

Important Dates

Submission DeadlineAugust 31, 2019
First Round of ReviewNovember 30, 2019
Publication DateJanuary, 2020