Abstract: Geeta distribution is a new discrete random variable distribution defined over all the positive integers with two parameters. This distribution belongs to the family of Location-parameter (LDPD) system and is of the form L – shaped model. Pareto and Yule distributions belong to the same family but these distributions have a disadvantage of having a single parameter which makes them not versatile to meet the needs of modern complex data sets. Geeta distribution is found to be very versatile and flexible to fit observed count data sets and can be used efficiently to model different types of sets. This paper investigates the characteristics of Geeta distribution, such as the existence of the mean, variance, moment generating function, probability generating function and that the sum of probabilities for all values of X for Geeta Distribution model is unity. It is well known that the sample mean is the estimator of a population mean from a given population of interest as a point estimator which assume a single number that is obtained by taking a random sample of a specified size from the entire population, depending on whether the population mean and variance is known or unknown These point estimators were obtained by employing the method of Moments, Maximum Likelihood (MLE) and Bayesian estimator. Further the estimators were subjected to the conditions like unbiasedness, efficiency, sufficiency and completeness which are properties of a good estimator. For the first aspect, the results of the mean, variance, moments and generating functions were achieved that proves the distribution is a probability density function (pdf). The methods of moments and the maximum likelihood and their properties were applied and yielded the desired and expected results for any given probability distribution. The best estimator obtained is best linear unbiased estimator (BLUE).Abstract: Geeta distribution is a new discrete random variable distribution defined over all the positive integers with two parameters. This distribution belongs to the family of Location-parameter (LDPD) system and is of the form L – shaped model. Pareto and Yule distributions belong to the same family but these distributions have a disadvantage of having a...Show More
Abstract: Exchange rates and monetary policies are key tools in economic management and in the stabilization and adjustment process in developing countries, where low inflation rates and international competitiveness have become major policy targets. The study modelled the volatility of the US dollar against the Kenyan shilling (USD/KES) exchange rate and investigated the effect of inflation rates in Kenya on this volatility for the years 2005 to 2017. The data for this research was obtained from secondary sources: Central Bank of Kenya and the Kenya National Bureau of Statistics. The results indicated that the USD/KES exchange rate exhibited persistent signs of volatility. A number of heteroscedasticity models were then tested and the GARCH family (ARMA (1, 3)/EGARCH (1, 2)) model was concluded to be the best model to fit the volatility of the USD/KES exchange rate. The study tested the forecasting power of this model by comparing in-sample and out of sample observations and comprehensive conclusions were made that the model was the best fit to forecast the volatility of the USD/KES exchange rate. The volatility figures of the USD/KES exchange rate were extracted from the EGARCH model and further tests were conducted to investigate the effect of Kenyan inflation rates on them. Weighted Least Squares regression was conducted on the Kenyan inflation rates and volatility of the USD/KES exchange rate and comprehensive conclusions were made that there existed a significant relationship between the Kenyan inflation rates and the volatility of the USD/KES.Abstract: Exchange rates and monetary policies are key tools in economic management and in the stabilization and adjustment process in developing countries, where low inflation rates and international competitiveness have become major policy targets. The study modelled the volatility of the US dollar against the Kenyan shilling (USD/KES) exchange rate and in...Show More