The lognormal distribution is useful in modeling continuous random variables which are greater than or equal to zero. Example scenarios in which the lognormal distribution is used include, among many others: in medicine, latent periods of infectious diseases; in environmental science, the...

The beta distribution is useful in modeling continuous random variables that lie between 0 and 1, such as proportions and percentages. The beta distribution takes on many different shapes and may be described by two shape parameters, alpha and beta, that can be difficult to estimate. Maximum...

This dissertation consists of three essays on modeling and parameter estimation for covariance non-stationary processes. The first essay considers the non-linear deformation of time scale for G(lambda)-stationary processes developed by Jiang, Gray and Woodward [2006]. After the appropriate...

This paper proposes different investment strategies for portfolio selection based on decision-making under uncertainty, rather than the conventional Markowitz portfolio model. The results of perfectinformation and the results of investment strategies for decision-making under uncertainty are...

(Keine Zusammenfassung in deutscher Sprache vorhanden.) (No summary in German language.)