Symposium on Statistical & Computational Modelling with Applications (SymSCMA)

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Author: search.filters.author.Perera, S.S.N.

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    2-Tuple Fuzzy Linguistic Model to Evaluate the Risk of Invasive Plant Species
    (Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka, 2016) Peiris, H.O.W.; Perera, S.S.N.; Chakraverty, S.; Ranwala, S.M.W.
    Management of invasive species can appear to be a complicated and unending task. In order to manage the spread, these species need to be undergone any risk assessment during their introduction. The aim of this study is to evaluate the aggregate risk of Invasive Alien Species (IAS) using invasive attributes. We use the 2-tuple fuzzy linguistic representation to develop the model without loss of information in which occur in ordinary linguistic operators. These risk values are compared with the National Risk assessment scores which are in the form of Linguistic labels. The proposed model is validated using few known noninvasive species in Sri Lanka. The model gives significant predictions and it is found to be a better tracking system for identifying potential invaders than the conventional risk assessment methods.
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    Analysis of Factors Affecting USD/LKR Exchange Rate
    (Department of Statistics & Computer Science, University of Kelaniya, Sri Lanka, 2016) Jayasuriya, D.P.S.H.; Perera, S.S.N.
    This paper intends to investigate the factors affecting the US Dollar exchange rate in Sri Lanka, in the period of January 2009 to June 2015, by using the econometric framework of Johanson and Juselius Cointegration, Vector Auto Regressive model, Granger Causality, and Variance Decomposition analysis. The empirical results of the model indicate that the increase in previous month net foreign assets and trade balance, and a decrease in the previous month exchange rate, has a significant influence on the short run appreciation of exchange rate. Granger Causality test confirms past values of net foreign assets, trade balance, and workers’ remittance have a predictive ability in determining the present values of exchange rate while, Variance Decomposition indicate, variation in exchange rate in short term and long term time horizon is due to the exchange rate itself and net foreign assets, trade balance and workers’ remittance respectively.