arXiv research

New methods improve estimation of nonhomogeneous Poisson processes from limited data.

A new method estimates nonhomogeneous Poisson process intensities with super-resolution.

The article extends previous work on contracting convex hypersurfaces by nonhomogeneous curvature functions.

We present simple examples of finite-dimensional connected homogeneous spaces (they are actually topological manifolds) with nonhomogeneous and nonrigid factors. In particular, we give an elementary solution of an old problem in general topology concerning homogeneous spaces.

Optimal fund deployment strategy under uncertain deal arrivals.

The paper studies how convex hypersurfaces in hyperbolic space evolve under a specific curvature flow.

Novel unsupervised MIG detectors improve signal detection in cluttered environments.

New nonparametric HMM improves genetic sequence analysis.

This chapter is an attempt to present a mathematical theory of compound fractional Poisson processes. The chapter begins with the characterization of a well-known Lévy process: The compound Poisson process. The semi-Markov extension of the compound Poisson process naturally leads to the compound fractional Poisson proc…

New model distinguishes Poisson processes from self-similar ones.

Flexible nonlinear Hawkes processes for time-varying systems.

We describe 4th order ODEs satisfying two contact invariant conditions of Bryant in terms of the Ricci tensor of a certain gl(2,R) valued connection. We also provide nonhomogeneous examples of such ODEs.

We show that the stick-breaking construction of the beta process due to Paisley, et al. (2010) can be obtained from the characterization of the beta process as a Poisson process. Specifically, we show that the mean measure of the underlying Poisson process is equal to that of the beta process. We use this underlying re…

The fractional Poisson process (FPP) is a counting process with independent and identically distributed inter-event times following the Mittag-Leffler distribution. This process is very useful in several fields of applied and theoretical physics including models for anomalous diffusion. Contrary to the well-known Poiss…

A deep Neyman-Scott process uses Poisson processes for efficient inference in complex point processes.

Let $f,g:{\Bbb R}\to{\Bbb R}$ be integrable functions, $f$ nowhere zero, and $φ(u)=\int du/f(u)$ be invertible. An exact solution to the generalized nonhomogeneous inviscid Burgers' equation $u_t+g(u).u_x=f(u)$ is given, by quadratures.

A beta-negative binomial (BNB) process is proposed, leading to a beta-gamma-Poisson process, which may be viewed as a "multi-scoop" generalization of the beta-Bernoulli process. The BNB process is augmented into a beta-gamma-gamma-Poisson hierarchical structure, and applied as a nonparametric Bayesian prior for an infi…

Study shows convergence rates for BSDEs approximated by compound Poisson processes.

New method models Poisson intensity using RKHS for high-dimensional data.

The common assertion that the Ricci flows of Einstein spaces with cosmological constant can be modelled by certain classes of nonholonomic frame, metric and linear connection deformations resulting in nonhomogeneous Einstein spaces is examined in the light of the role played by topological three dimensional (3D) Taub-N…

Proposes a model for predicting events from event streams.

Study shows Merton model limits to Poisson process with log-normal intensity, improving default portfolio prediction.

Several possible notions of Hardy-Sobolev spaces on a Riemannian manifold with a doubling measure are considered. Under the assumption of a Poincaré inequality, the space $\Mone$, defined by Hajłasz, is identified with a Hardy-Sobolev space defined in terms of atoms. Decomposition results are proved for both the homoge…

The study examines evolving star-shaped hypersurfaces in hyperbolic spaces, influenced by ambient geometry.

Paper improves fraud detection in imbalanced financial data.

Study of bandit problem with Poisson decision times and Lévy processes.

Efficiently infers Poisson process intensity using Gaussian process with sigmoid link.

Random geodesics on curved surfaces form a pattern similar to random lines.

We analyse the dynamics of the Warsaw Stock Exchange index WIG at a daily time horizon before and after its well defined local maxima of the cusp-like shape decorated with oscillations. The rising and falling paths of the index peaks can be described by the Mittag-Leffler function superposed with various types of oscil…

We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of the time series. The process is composed of consecutive patches of variable length, each patch being described by a station…

We present a probabilistic model of events in continuous time in which each event triggers a Poisson process of successor events. The ensemble of observed events is thereby modeled as a superposition of Poisson processes. Efficient inference is feasible under this model with an EM algorithm. Moreover, the EM algorithm …

Establishes a microstructural foundation for a rough log-normal volatility model.

A new Bayesian optimization method using Poisson process for better noise robustness.

A bandit problem with filtered Poisson process data.

Study of lengths of cycles in large genus random maps converging to Poisson process.

We study the geometric quantization process for twisted Poisson manifolds. First, we introduce the notion of Lichnerowicz-twisted Poisson cohomology for twisted Poisson manifolds and we use it in order to characterize their prequantization bundles and to establish their prequantization condition. Next, we introduce a p…

This paper solves mapping problems with a novel Gibbs sampling method.

Modeling trading volume curves using hierarchical Poisson processes.

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process f…

Enhances count process modelling with Markov-modulated non-homogeneous Poisson process.

Study on critical faces convergence in a Poisson point process.

Efficient variational inference for Gaussian-process-modulated Poisson processes with panel count data.

In this note we study the optimal dividend problem for a company whose surplus process, in the absence of dividend payments, evolves as a generalized compound Poisson model in which the counting process is a generalized Poisson process. This model including the classical risk model and the Polya-Aeppli risk model as sp…

This paper discusses properties of a Doubly Stochastic Poisson Process (DSPP) where the intensity process belongs to a class of affine diffusions. For any intensity process from this class we derive an analytical expression for probability distribution functions of the corresponding DSPP. A specification of our results…

A new kernel method improves Poisson process intensity estimation.

A model for the phenomenological description of tick-by-tick share prices in a stock exchange is introduced. It is based on mixtures of compound Poisson processes. Preliminary results based on Monte Carlo simulation show that this model can reproduce various stylized facts.

We study optimal trade execution strategies in financial markets with discrete order flow. The agent has a finite liquidation horizon and must minimize price impact given a random number of incoming trade counterparties. Assuming that the order flow $N$ is given by a Poisson process, we give a full analysis of the prop…

New model estimates higher-order interactions in stochastic processes using lower-dimensional projections.