Filtered statistical models and Hellinger processes
نویسندگان
چکیده
منابع مشابه
Efficient Hellinger distance estimates for semiparametric models
Minimum distance techniques have become increasingly important tools for solving statistical estimation and inference problems. In particular, the successful application of the Hellinger distance approach to fully parametric models is well known. The corresponding optimal estimators, known as minimum Hellinger distance estimators, achieve efficiency at the model density and simultaneously posse...
متن کاملInformation Processes in Filtered Experiments
In this paper we give explicit representations for Kullback-Leibler information numbers between a priori and a posteriori distributions, when the observations come from a semimartingale. We assume that the distribution of the observed semimartingale is described in terms of the so-called triplet of predictable characteristics. We end by considering the corresponding notions in a model with a fr...
متن کاملThe Role of Hellinger Processes in Mathematical Finance
This paper illustrates the natural role that Hellinger processes can play in solving problems from finance. We propose an extension of the concept of Hellinger process applicable to entropy distance and f -divergence distances, where f is a convex logarithmic function or a convex power function with general order q, 0 6= q < 1. These concepts lead to a new approach to Merton’s optimal portfolio...
متن کاملHellinger distance
In this lecture, we will introduce a new notion of distance between probability distributions called Hellinger distance. Using some of the nice properties of this distance, we will generalize the fooling set argument for deterministic protocols to the randomized setting. We will then use this to prove a Ω(n) lower bound for the communication complexity of Disjointness. We will also see how this...
متن کاملThe Statistical Properties of Filtered Signals
In this paper, the statistical properties of filtered or convolved signals are considered by deriving the resulting density functions as well as the exact mean and variance expressions given a prior knowledge about the statistics of the individual signals in the filtering or convolution process. It is shown that the density function after linear convolution is a mixture density, where the numbe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 1989
ISSN: 0304-4149
DOI: 10.1016/0304-4149(89)90052-5