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The classical binomial process has been studied by \citet{jakeman} (and the references therein) and has been used to characterize a series of radiation states in quantum optics. In particular, he studied a classical birth-death process…

Probability · Mathematics 2020-12-11 Dexter O. Cahoy , Federico Polito

The paper proposes a formal estimation procedure for parameters of the fractional Poisson process (fPp). Such procedures are needed to make the fPp model usable in applied situations. The basic idea of fPp, motivated by experimental data…

Methodology · Statistics 2018-06-08 Dexter Cahoy , Vladimir V. Uchaikin , Wojbor A. Woyczynski

In this paper, we define a fractional negative binomial process (FNBP) by replacing the Poisson process by a fractional Poisson process (FPP) in the gamma subordinated form of the negative binomial process. First, it is shown that the…

Probability · Mathematics 2014-10-08 P. Vellaisamy , A. Maheshwari

The fractional birth and the fractional death processes are more desirable in practice than their classical counterparts as they naturally provide greater flexibility in modeling growing and decreasing systems. In this paper, we propose…

Statistics Theory · Mathematics 2014-06-30 Dexter O. Cahoy , Federico Polito

We consider a fractional counting process with jumps of amplitude $1,2,\ldots,k$, with $k\in \mathbb{N}$, whose probabilities satisfy a suitable system of fractional difference-differential equations. We obtain the moment generating…

Probability · Mathematics 2016-03-10 Antonio Di Crescenzo , Barbara Martinucci , Alessandra Meoli

We study the long-range dependence (LRD) of the increments of the fractional Poisson process (FPP), the fractional negative binomial process (FNBP) and the increments of the FNBP. We first point out an error in the proof of Theorem 1 of…

Probability · Mathematics 2016-01-21 A. Maheshwari , P. Vellaisamy

We study a fractional birth-death process with state dependent birth and death rates. It is defined using a system of fractional differential equations that generalizes the classical birth-death process introduced by Feller (1939). We…

Probability · Mathematics 2024-10-24 K. K. Kataria , P. Vishwakarma

Traditionally, fractional counting processes, such as the fractional Poisson process, etc. have been defined using fractional differential and integral operators. Recently, Laskin (2024) introduced a generalized fractional counting process…

Probability · Mathematics 2024-12-06 Shilpa Garg , Ashok Kumar Pathak , Aditya Maheshwari

Recently, a generalized Bernoulli process (GBP) was developed as a stationary binary sequence whose covariance function obeys a power law. In this paper, we further develop generalized Bernoulli processes, reveal their asymptotic behaviors,…

Probability · Mathematics 2023-11-21 Jeonghwa Lee

In this paper, we introduce a generalized fractional negative binomial process (GFNBP) by time changing the fractional Poisson process with an independent Mittag-Leffler (ML) Levy subordinator. We study its distributional properties and its…

Probability · Mathematics 2023-04-21 Ritik Soni , Ashok Kumar Pathak

In this article, we provide different representations for a time-fractional birth and death process $N_{\alpha}(t)$, whose transition probabilities are governed by a time-fractional system of differential equations. More specifically, we…

Probability · Mathematics 2020-04-30 Jorge Littin

Many real time-series exhibit behavior adequate to long range dependent data. Additionally very often these time-series have constant time periods and also have characteristics similar to Gaussian processes although they are not Gaussian.…

Data Analysis, Statistics and Probability · Physics 2017-01-04 A. Kumar , A. Wyłomańska , R. Połoczański , S. Sundar

We introduce and study a fractional variant of the linear birth-death process, namely, the generalized fractional linear birth-death process (GFLBDP) which is defined by taking the regularized Hilfer-Prabhakar derivative in the system of…

Probability · Mathematics 2025-02-12 Manisha Dhillon , Pradeep Vishwakarma , Kuldeep Kumar Kataria

Approximations of fractional Brownian motion using Poisson processes whose parameter sets have the same dimensions as the approximated processes have been studied in the literature. In this paper, a special approximation to the…

Statistics Theory · Mathematics 2012-01-05 Yuqiang Li , Hongshuai Dai

Within the context of the binomial model, we analyse sequences of values that are almost-uniform and we discuss a prediction method called the frequent outcome approach, in which the outcome that has occurred the most in the observed trials…

Statistics Theory · Mathematics 2022-09-29 Ben O'Neill

In this paper, we propose some representations of a generalized linear birth process called fractional Yule process (fYp). We also derive the probability distributions of the random birth and sojourn times. The inter-birth time distribution…

Probability · Mathematics 2014-03-06 Dexter O. Cahoy , Federico Polito

We present a purely deep neural network-based approach for estimating long memory parameters of time series models that incorporate the phenomenon of long-range dependence. Parameters, such as the Hurst exponent, are critical in…

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour

In this paper, we introduce and study a convoluted version of the time fractional Poisson process by taking the discrete convolution with respect to space variable in the system of fractional differential equations that governs its state…

Probability · Mathematics 2021-07-20 K. K. Kataria , M. Khandakar

In this paper, we introduce a generalized birth process (GBP) which performs jumps of size $1,2,\dots,k$ whose rates depend on the state of the process at time $t\geq0$. We derive a non-exploding condition for it. The system of differential…

Probability · Mathematics 2021-10-05 K. K. Kataria , M. Khandakar
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