Inverse problems can be described as functional equations where the value of the function
is known or easily estimable but the argument is unknown. Many problems in econometrics …

This paper reviews issues, models, and methodologies arising out of the problems of
predicting earthquakes and forecasting earthquake risk. The emphasis is on statistical …

Spatial point processes play a fundamental role in spatial statistics and today they are an
active area of research with many new applications. Although other published works …

In financial and actuarial modeling and other areas of application, stochastic differential
equations with jumps have been employed to describe the dynamics of various state …

Statistical Inference for Ergodic Diffusion Processes encompasses a wealth of results from
over ten years of mathematical literature. It provides a comprehensive overview of existing …

Be they random or non-random, iterative methods have progressively gained sway with the
development of computer science and automatic control theory. Thus, being easy to …

Maintaining the excellent features that made the first edition so popular, this outstanding
reference/text presents the only comprehensive treatment of the theory of point processes …

We consider three different martingale estimating functions based on discrete-time
observations of a diffusion process. One is the discretized continuous-time score function …

Parameter estimation in stochastic differential equations and stochastic partial differential
equations is the science, art and technology of modelling complex phenomena and making …

The maximum likelihood estimation of the unknown parameter of a diffusion process based
on an approximate likelihood given by the discrete observation is treated when the diffusion …