Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains v, 30 p. Includes abstract. Includes bibliographical references (p. 29-30).

published_or_final_version / Mathematics / Master / Master of Philosophy

published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

In the actuarial literature, dependence structures in risk models have been extensively studied. The main theme of this thesis is to investigate some discrete-time risk models with claim numbers modeled by integer-valued time series processes. The first model is a common shock risk model with temporal dependence between the claim numbers in each individual class of business. Specifically the Poisson MA(1) process and Poisson AR(1) process are considered for the temporal dependence. To study the ruin probability, the equations associated with the adjustment coefficients are derived. Comparisons are also made to assess the impact of the dependence structures on the ruin probability. Another model involving both the correlated classes of business and the time series approach is then studied. Thinning dependence structure is adopted to model the dependence among classes of business. The Poisson MA(1) and Poisson AR(1) processes are used to describe the claim-number processes. Adjustment coefficients and ruin probabilities are examined. Finally a discrete-time risk model with the claim number following a Poisson ARCH process is proposed. In this model, the mean of the current claim number depends on the previous observations. Within this framework, the equation for finding the adjustment coefficient is derived. Numerical studies are also carried out to examine the effect of the Poisson ARCH dependence structure on several risk measures including ruin probability, Value at Risk, and conditional tail expectation. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

This video series and report act as an educational tool to help small to mid-sized nonprofits use social media in the most beneficial way for their organization, by offering advice and tactics based on actual stories from nonprofits in Austin, Texas. As the landscape of marketing and media changes, nonprofits must be willing to utilize social media for their development strategies, event planning, volunteer recruitment and engagement, and have an up to date social media policy. Six nonprofit organizations tell their success stories and discuss the importance of integrating social media into their marketing strategies and campaigns. / text

Abstract A powerful tool for bearing time series feature extraction and classification is introduced that is computationally inexpensive, easy to implement and suitable for real-time applications. In this paper the proposed technique is applied to two rolling element bearing time series classification problems and shown that in some cases no data pre-processing, artificial neural network or nearest neighbour approaches are required. From the results obtained it is clear that for the specific applications considered, the proposed method performed as well as or better than alternative approaches based on conventional feature extraction.

This paper examines trade openness and economic growth. What has been the effect of openness to trade on economic growth in Kenya? Kenya’s trade policies have emerged since independence, it has improved from import substitution to progressive liberalization through emergence of export processing zones, reduction of tariffs levels, eliminated price controls and licensing requirements leading to modest growth in trade Republic of Kenya (2005). Although the country has improved in it’s trade policies, it is still counted as mostly unfree. Empirical evidence suggests that free trade leads to a better economic performance in different channels, however the evidence has been questioned because of the doubts on how trade openness of a country should be measured and methodology estimation. The study uses trade intensity as a measure of trade openness. Applying Ordinary least squares using a time series data obtained from the World Development Indicators a negative relationship is seen between trade openness measure and Gross domestic product in Kenya. A Granger causality test is done also to determine whether trade liberalization can be used to give significant information about the economic growth of Kenya or vice versa. Vector Auto regression model (VAR) is used to determine the Granger causality. In the OLS regression model measures of openness, labor and capital are significant.

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published_or_final_version / Applied Statistics / Master / Master of Social Sciences

published_or_final_version / abstract / toc / Statistics / Master / Master of Philosophy