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Related papers: Point processes in a metric space

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The extreme event statistics plays a very important role in the theory and practice of time series analysis. The reassembly of classical theoretical results is often undermined by non-stationarity and dependence between increments.…

Statistical Finance · Quantitative Finance 2015-05-28 Mauro Politi , Nicolas Millot , Anirban Chakraborti

When a spatial process is recorded over time and the observation at a given time instant is viewed as a point in a function space, the result is a time series taking values in a Banach space. To study the spatio-temporal extremal dynamics…

Probability · Mathematics 2010-01-20 Thomas Meinguet , Johan Segers

This paper provides the basis for new methods of inference for max-stable processes \xi\ on general spaces that admit a certain incremental representation, which, in important cases, has a much simpler structure than the max-stable process…

Probability · Mathematics 2012-09-12 Sebastian Engelke , Alexander Malinowski , Marco Oesting , Martin Schlather

Metric search is concerned with the efficient evaluation of queries in metric spaces. In general,a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query…

Information Retrieval · Computer Science 2017-10-24 Richard Connor , Lucia Vadicamo , Franco Alberto Cardillo , Fausto Rabitti

Partially observable Markov decision processes (POMDPs) have recently become popular among many AI researchers because they serve as a natural model for planning under uncertainty. Value iteration is a well-known algorithm for finding…

Artificial Intelligence · Computer Science 2011-06-02 N. L. Zhang , W. Zhang

We consider stochastic point processes generating time series exhibiting power laws of spectrum and distribution density (Phys. Rev. E 71, 051105 (2005)) and apply them for modeling the trading activity in the financial markets and for the…

Data Analysis, Statistics and Probability · Physics 2015-05-18 B. Kaulakys , M. Alaburda , V. Gontis

The magnitude of a finite metric space has recently emerged as a novel invariant quantity, allowing to measure the effective size of a metric space. Despite encouraging first results demonstrating the descriptive abilities of the magnitude,…

Machine Learning · Computer Science 2024-07-08 Michael F. Adamer , Edward De Brouwer , Leslie O'Bray , Bastian Rieck

In this paper, the Mean value iterative process is modified with the Mann iterative process for mean nonexpansive mapping in a hyperbolic metric space that satisfy the symmetry criteria and in uniformly convex hyperbolic spaces to validate…

Functional Analysis · Mathematics 2025-05-12 Mohd Tariq , Mayank Sharma

This thesis is devoted to the study of extreme value statistics in stochastic processes and their applications. In the first part, we obtain exact analytical results on the extreme value statistics of both discrete-time and continuous-time…

Statistical Mechanics · Physics 2023-10-24 Benjamin De Bruyne

Predicting when and where events will occur in cities, like taxi pick-ups, crimes, and vehicle collisions, is a challenging and important problem with many applications in fields such as urban planning, transportation optimization and…

Machine Learning · Statistics 2019-06-24 Maya Okawa , Tomoharu Iwata , Takeshi Kurashima , Yusuke Tanaka , Hiroyuki Toda , Naonori Ueda

Hawkes Processes are a type of point process which models self-excitement among time events. It has been used in a myriad of applications, ranging from finance and earthquakes to crime rates and social network activity analysis.Recently, a…

Machine Learning · Computer Science 2021-01-05 Rafael Lima

In order to describe the extremal behaviour of some stochastic process $X$, approaches from univariate extreme value theory are typically generalized to the spatial domain. In particular, generalized peaks-over-threshold approaches allow…

Methodology · Statistics 2026-01-01 Max Thannheimer , Marco Oesting

The influence of errors on the convergence of infinite products of weak quasi-contraction mappings in $b$-metric spaces is explored. An example demonstrating the necessity of convergence of the sequence of computational errors to zero is…

Functional Analysis · Mathematics 2020-02-06 Anuradha Gupta , Manu Rohilla

A spatial point process can be characterized by an intensity function which predicts the number of events that occur across space. In this paper, we develop a method to infer predictive intensity intervals by learning a spatial model using…

Machine Learning · Statistics 2020-07-06 Muhammad Osama , Dave Zachariah , Petre Stoica

We introduce a point process regression model that is applicable to price models and limit order book models. Hawkes type autoregression in the intensity process is generalized to a stochastic regression to covariate processes. We establish…

Statistics Theory · Mathematics 2015-12-08 Teppei Ogihara , Nakahiro Yoshida

We construct a general procedure for the Quasi Likelihood Analysis applied to a multivariate point process on the real half line in an ergodic framework. More precisely, we assume that the stochastic intensity of the underlying model…

Statistics Theory · Mathematics 2016-09-28 Simon Clinet , Nakahiro Yoshida

Human activities generate various event sequences such as taxi trip records, bike-sharing pick-ups, crime occurrence, and infectious disease transmission. The point process is widely used in many applications to predict such events related…

Machine Learning · Computer Science 2024-01-30 Yoshiaki Takimoto , Yusuke Tanaka , Tomoharu Iwata , Maya Okawa , Hideaki Kim , Hiroyuki Toda , Takeshi Kurashima

A field with an absolute value function is a basic type of metric space, which includes the real and complex numbers with their standard metrics, and ultrametrics on fields like the p-adic numbers. Here we try to give some perspectives of…

Classical Analysis and ODEs · Mathematics 2014-03-31 Stephen Semmes

Consider $n$ i.i.d. random elements on $C[0,1]$. We show that, under an appropriate strengthening of the domain of attraction condition, natural estimators of the extreme-value index, which is now a continuous function, and the normalizing…

Statistics Theory · Mathematics 2007-06-13 John H. J. Einmahl , Tao Lin

We show that for a large class of marked point processes there exists a random measure m with the predictable representation property such that iterated integrals with respect to m span the space of square integrable random variables.

Probability · Mathematics 2011-10-05 Samuel N. Cohen