Nigerian Young Academy (NYA) Call for Membership

Applications 2019:

The call is open to all scholars working in any research-based discipline, including the social sciences, arts, humanities, education, law, sciences, medicine, engineering etc...Read More


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Title of highest degree: PhD English

Institutional Affiliation: Redeemer's University, Ede, Nigeria

Awards, fellowships and distinctions:

(i) Alexander von Humboldt Research Fellowship, 2015-2016

(ii) Alexander von Humboldt Return Fellowship, 2016-2017

Current research areas: Corpus (Pragmatics) and Discourse Analysis







DATE: Tuesday 19th - Thursday 21st June 2018

VENUE: Federal University of Technology, Akure, Nigeria

1. Background/Preamble

Regression is the most popular and commonly used statistical methodology for analyzing empirical problems in social sciences, economics, and life sciences. Recently, there has been tremendous advances in regression modelling where the traditional assumptions underlying generalized linear models (linear impact of covariates, independence of observations, univariate exponential family for the response) can be relaxed. Semiparametric regression models have been extended in several directions, for example with the inclusion of spatial effects that account for spatial correlations. There is also the possibility of relating higher moments of the response distribution, aside the mean, to available covariates through distributional regression. The workshop aims at presenting some recent advances in distributional semiparametric regression in a unifying, Bayesian perspective.

2. Objectives of the course
At the end of the course, the participants are expected to:

i. develop and apply semiparametric and spatial regression models

ii. develop and utilize distributional spatial models to link higher moments of the response distribution to covariates

iii. adopt spatial models to analyze spatial patterns of any demographic, health or related issues of interest.

iv. extend the notion of spatial models to time-to-event datasets via survival analysis models.

v.. implement spatial and semi-parametric models in statistical software such as BayesX and R.

3. Target participants

The target participants are researchers and postgraduate students in any area of statistical science and allied courses or those who develop an appreciable interest in statistics.

4. Prerequisites

Participants are expected to have some basic knowledge of regression analysis and multivariate statistics. Software to be utilized during the training are R, BayesX and Stata/SPSS.

5. Course Outline

Topics to be covered include:

Ø Regression Models (Linear models, Mixed models, Additive Models, Generalized Additive Models)

Ø Structure Additive Models

Ø Spatial Models for Nonnegative, Zero-inflated and Categorical Responses

Ø Distributional Spatial Regression

Ø Bayesian Estimation of Spatial Models

Ø Geoadditive survival models

Ø Data Cleansing and Coding for Spatial Analysis

Ø An Overview of Fitting Spatial Models in R and BayesX

Ø Practical hands-on sessions using DHS data sets

6. Venue and Date

The venue of the workshop is FUTA-LISA Lab., Academic Building, Federal University of Technology, Akure from Tuesday 19th of June to Thursday, 21st of June, 2018.

7. Pre-Registration Workshop Fee

Interested participants are expected to freely preregister by completing the application form at on or before 1st of June, 2018.

All enquiries should be made through:This email address is being protected from spambots. You need JavaScript enabled to view it..

Follow updates via the NYA website:

The workshop fee is N10,000 per selected participant.
Certificate of participation would be issued at the end of the course.

8. Profile of the Facilitators

1. Dr. Ezra Gayawan, FNYA

Ezra Gayawan teaches statistics at The Federal University of Technology, Akure, Nigeria. He earned a PhD in Statistics from University of Ilorin, Nigeria and was a postdoctoral fellow at Universidade Federal de Minas Gerias, Brazil. His research interests include spatial and spatiotemporal statistics, Bayesian semiparametric models, and modelling of epidemiology and demographic social issues. He has published several articles in these areas in leading international journals. He has also co-authored a chapter in the book Advance Techniques for Modelling Maternal and Child Health in Africa, published by Springer. He has presented papers in several national and international conferences and has served as a facilitator in several workshops organized by the Nigerian Young Academy (NYA), National Mathematical Centre (MNC) among others. He is a member of several professional organizations including the Nigerian Statistical Association (NSA), International Statistical Institute (ISI), Institute of Mathematical Statistics (IMS) and the Population Association of America (PAA). His work has earned him several travel and research grants as well as a fellowship. He is a Fellow of the Nigerian Young Academy.

2. Samson B. Adebayo earned his PhD in Statistics at the Ludwig Maximilian University of Munich. A recipient of DAAD scholarship, his research interest focuses on Spatial and semiparametric models; Bayesian models and Demographic and Health issues analysis. He has authored several articles that have appeared in leading national and international journals covered by Thomson Reuters. He has also contributed to chapters in a book published by Springer. He has taught statistics and supervised students at all levels in Universities both in Nigeria and the UK. Currently, he is Director of Planning, Research and Statistics, National Agency for Food and Drug Administration and Control (NAFDAC) and a visiting Professor, Nasarawa State University, Keffi.


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