PARAMETRIC AND NON-PARAMETRIC STATISTICAL TECHNIQUES TO INVESTIGATE FISHERIES DATA IN LAKE NASSER EGYPT

Abstract

Much attention has been given to the economic aspects of the fisheries in Egypt, while building a statistical model for fish production has received little attention. This study is devoted to a comprehensive assessment of Lake Nasser fisheries; past, present and future. Lake Nasser is one of the main fisheries resources in Egypt, and there is an evidence that the fisheries have been overexploited in recent years. The study objectives were to determine the factors that affect fish catches and compare between parametric and non-parametric models of the fish catches. Two ways of modelling the fish catch (dependent variable) against number of fishermen, number of boats and the highest level and lowest level of water in the lake (independent variables). These two ways are parametric and non-parametric models. These two models are ARIMA model with explanatory variables as parametric model and generalized additive model GAM as non-parametric. GAM gave an improved fit to the time series data compared with the parametric analysis.