In this paper, we suggest and analyze a new class of specification tests for random
coefficient models. These tests allow to assess the validity of central structural features of the …

This paper develops an unbiased Monte Carlo approximation to the transition density of a
jump–diffusion process with state-dependent drift, volatility, jump intensity, and jump …

This paper is concerned with parametric estimation, model specification and autocorrelation
diagnosis for stationary moving averages driven by a Wiener process. By incorporating the …

Probability transform-based inference, for example, characteristic function-based inference,
is a good alternative to likelihood methods when the probability density function is …

This dissertation is devoted to statistical inference based on characteristic functions. For
some popular stochastic processes (eg, Lévy processes, Lévy driven Ornstein-Uhlenbeck …

Multivariate Linnik distributions, despite their potential usefulness, have not been well-
studied due to their di culty in nding representations and estimators. Pa-rameter estimation …

This thesis studies the estimation, goodness-of-fit testing, pricing and sampling problems for
regime switching models, which are popularly used in financial markets. Specifically, we …

Abstract Single Particle Tracking (SPT) data can aid in understanding a variety of complex
spatio-temporal processes (eg, chromatin remodeling in the nucleus). However, quantifying …