Random population dynamics with catastrophes (events pertaining to possible elimination of
a large portion of the population) has a long history in the mathematical literature. In this …

Disturbances have been recognized as a key factor shaping terrestrial ecosystem states and
dynamics. A general model that quantitatively describes the relationship between carbon …

We study processes that consist of deterministic evolution punctuated at random times by
disturbances with random severity; we call such processes semistochastic. Under …

The problem of controlling stationarity involves an important aspect of forecasting, in which a
time series is analyzed in terms of levels or differences. In the literature, non-parametric …

Establishment of a long-term biological population management policy requires balancing
its cost and utility/disutility. We approach this issue from the viewpoint of stochastic control as …

In this paper, a Data Mining of real times series data using Self-correlation Coefficients is
investigated. The standard KPSS method was performed on real Time Series Data, in an …

Forest-fire and avalanche models support the notion that frequent catastrophes prevent the
growth of very large populations and as such, prevent rare large-scale catastrophes. We …

In this paper we propose an algorithm to numerically simulate Markov processes of jump
type. While these processes can naturally be generated as solutions to jump-SDEs the …

The primary objects of study in this dissertation are semistochastic processes. The types of
semistochastic processes we consider are continuous-time and continuous-state processes …