Vincent Marmara

Vincent Marmarà

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Personal

I did my undergraduate, B.Sc.(Hons) degree at The University of Malta in Mathematics, Statistics and Operational Research. I completed my M.Sc. in Statistics with Sheffield University in 2009 and currently doing a PhD in Mathematics under the supervision of Dr Adam Kleczkowski (Stirling University). Currently I’m an assistant Lecturer at the University of Malta and working as a Business Intelligence Commercial Analyst with Betfair.

Research

My main areas of research are Epidemiology, Missing Data, Bayesian Analysis, Sampling Techniques, Time Series and Regression Analysis.

Abstract: “The main aim of this dissertation is to study the problem of missing data in surveys. This study will lead us to analyze other issues related to nonresponse. In fact there are other aims in this dissertation. One of them is the discussion about the use of the characteristics of the population and sample, mainly demographic issues. These will be used for the implementation of imputation models. Imputation will be divided in two types; imputation to cater for respondents who refused to answer more than one question in the questionnaire, but not all of them and imputation to cater for those persons who refused to answer all the questions in the questionnaire. These analyses will be done with respect to two different kinds of surveys but three surveys for the analysis. Our main interests relate to be the classification of political tendencies of the nonrespondents. Another problem studied related to the estimation of income of nonrespondents. Finally we are going to compare and analyze the results obtained in this dissertation and also, further recommendations for further study.”

Abstract: “Ozone gas is a very influential gas in the earth’s atmosphere. This gas varies in various concentrations for different rural and urban areas. The level of concentration of ozone is influenced by the type of pollutants present in the atmosphere and other ambient conditions. In fact concentrations in rural areas are higher than in urban areas. This study investigated the relationship between urban and rural ozone concentrations and quantified the extent to which ambient rural conditions and the concentrations of other pollutants can be used to predict urban ozone concentrations. The general relationship between various levels of ozone concentrations at urban and neighbouring rural sites was explored using linear mixed-effect modelling and generalized least squares models. In these models the correlation and variance structures were defined so as to describe the error terms in the models due to dependent data. Ozone concentrations at finer temporal resolution are more dependent and have coarser resolution as well. During this study it was found that ozone concentrations coming from a neighbouring urban site make a better predictor to the urban ozone concentrations than ambient rural ozone at some levels of temporal averaging. Rural ozone was found to be the best predictor to predict urban ozone concentration for weekly average data. In general the constructed models produced good predictions for the urban ozone concentrations.”

I am at present the President of the Malta Statistics and Operations Research Organization (MSTOR) (Welcome to MSTOR). Our main aims are:

“The main aims of MSTOR are to promote unity among all statisticians and statistics students through social and educational activities and to promote the need of high quality research by means of seminars, conferences and other public activities. Other specific aims of the organization are to represent its members on a national and international level, to bridge the gap between academic life and industry and to empower statistics students with further resources complementary with what they are doing in their course.”