Random locations, ordered random sets and stationarity
نویسندگان
چکیده
منابع مشابه
Stationarity and random locations
We introduce a notion called “intrinsic location functional”. This is a large family of random locations including, for example, the location of the path supremum/infimum over an interval, the first/last hitting time, among many others. On one hand, it is proved that under stationarity, the distributions of intrinsic location functionals must satisfy the same very specific constraints, in spite...
متن کاملSearching in Random Partially Ordered Sets
We consider the problem of searching for a given element in a partially ordered set. More precisely, we address the problem of computing efficiently near-optimal search strategies for typical partial orders. We consider two classical models for random partial orders, the random graph model and the uniform model. We shall show that certain simple, fast algorithms are able to produce nearly-optim...
متن کاملThe Dimension of Random Ordered Sets
Let P = (X, <) be a finite ordered set and let I PI denote the cardinality of the universe X. Also let A(P) denote the maximum degree of P, i.e., the maximum number of points comparable to any one point of P. Fiiredi and Kahn used probabilistic methods to show that the dimension of P satisfies dim(P) I c,A(P) log(P1 and dim(P) 5 c,A(P) log2A(P) where c , and c, are positive absolute constants. ...
متن کاملOrdered Random Variables from Discontinuous Distributions
In the absolutely continuous case, order statistics, record values and several other models of ordered random variables can be viewed as special cases of generalized order statistics, which enables a unified treatment of their theory. This paper deals with discontinuous generalized order statistics, continuing on the recent work of Tran (2006). Specifically, we show that in general neither re...
متن کاملPropagation Models and Fitting Them for the Boolean Random Sets
In order to study the relationship between random Boolean sets and some explanatory variables, this paper introduces a Propagation model. This model can be applied when corresponding Poisson process of the Boolean model is related to explanatory variables and the random grains are not affected by these variables. An approximation for the likelihood is used to find pseudo-maximum likelihood esti...
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: 2016
ISSN: 0304-4149
DOI: 10.1016/j.spa.2015.10.004