scholarly journals Statistical properties of binomial and negative-binomial combinational optical field state and its generation in quantum diffusion channel

2015 ◽  
Vol 64 (8) ◽  
pp. 080303
Author(s):  
Fan Hong-Yi ◽  
Wu Ze
Keyword(s):  
Negative Binomial ◽  
Optical Field ◽  
Statistical Properties ◽  
Quantum Diffusion ◽  
Diffusion Channel ◽  
Field State

scholarly journals A new optical field state as an output of diffusion channel when the input being number state

2014 ◽  
Vol 57 (9) ◽  
pp. 1649-1653 ◽  
Author(s):  
HongYi Fan ◽  
SenYue Lou ◽  
XiaoYin Pan ◽  
LiYun Hu
Keyword(s):  
Optical Field ◽  
Diffusion Channel ◽  
Number State ◽  
Field State

scholarly journals Time evolution of negative binomial optical field in a diffusion channel

2015 ◽  
Vol 24 (9) ◽  
pp. 090302 ◽  
Author(s):  
Tang-Kun Liu ◽  
Pan-Pan Wu ◽  
Chuan-Jia Shan ◽  
Ji-Bing Liu ◽  
Hong-Yi Fan
Keyword(s):  
Time Evolution ◽  
Negative Binomial ◽  
Optical Field ◽  
Diffusion Channel

scholarly journals Maximum Product of Spacing Parameter Estimation of Gompertz Rayleigh Distribution and Application to Rainfall Datasets

2021 ◽  
pp. 41-59
Author(s):  
Hussein Ahmad Abdulsalam ◽  
Sule Omeiza Bashiru ◽  
Alhaji Modu Isa ◽  
Yunusa Adavi Ojirobe
Keyword(s):  
Goodness Of Fit ◽  
Negative Binomial ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Rainfall Data ◽  
Parameter Estimates ◽  
Data Sets ◽  
Unknown Parameters ◽  
Exponentiated Weibull ◽  
Integrated Hazard

Gompertz Rayleigh (GomR) distribution was introduced in an earlier study with few statistical properties derived and parameters estimated using only the most common traditional method, Maximum Likelihood Estimation (MLE). This paper aimed at deriving more statistical properties of the GomR distribution, estimating the three unknown parameters via a competitive method, Maximum Product of Spacing (MPS) and evaluating goodness of fit using rainfall data sets from Nigeria, Malaysia and Argentina. Properties of statistical distributions including distribution of smallest and largest order statistics, cumulative or integrated hazard function, odds function, rth non-central moments, moment generating function, mean, variance and entropy measures for GomR distribution were explicitly derived. The fitted data sets reveal the flexibility of GomR distribution over other distributions been compared with. Simulation study was used to evaluate the consistency, accuracy and unbiasedness of the GomR distribution parameter estimates obtained from the method of MPS. The study found that GomR distribution could not provide a better fit for Argentine rainfall data but it was the best distribution for the rainfall data sets from Nigeria and Malaysia in comparison with the distributions; Generalized Weibull Rayleigh (GWR), Exponentiated Weibull Rayleigh (EWR), Type (II) Topp Leone Generalized Inverse Rayleigh (TIITLGIR), Kumarawamy Exponential Inverse Raylrigh (KEIR), Negative Binomial Marshall-Olkin Rayleigh (NBMOR) and Exponentiated Weibull (EW). Furthermore, the estimates from MPSE were consistent as the sample size increases but not as efficient as those from MLE.

Statistical properties of the nonlinear negative binomial state

2007 ◽  
Vol 274 (2) ◽  
pp. 372-383 ◽  
Author(s):  
M. Sebawe Abdalla ◽  
A.-S.F. Obada ◽  
M. Darwish
Keyword(s):  
Negative Binomial ◽  
Statistical Properties ◽  
Binomial State

Statistical Properties of a System Consisting of a Superconducting Qubit Coupled to an Optical Field Inside a Transmission Line

2018 ◽  
Vol 69 (6) ◽  
pp. 727
Author(s):  
Clodoaldo Valverde ◽  
Gabriela Rodrigues Vaz ◽  
Vitor Teles de Oliveira ◽  
Basílio Baseia
Keyword(s):  
Transmission Line ◽  
Optical Field ◽  
Statistical Properties ◽  
Superconducting Qubit

STATISTICAL PROPERTIES OF RANDOMLY MODULATED PSEUDOTHERMAL OPTICAL FIELD

1971 ◽  
Vol 18 (12) ◽  
pp. 532-534 ◽  
Author(s):  
C. Bendjaballah ◽  
F. Perrot
Keyword(s):  
Optical Field ◽  
Statistical Properties

scholarly journals The Novel Bivariate Distribution: Statistical Properties and Real Data Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
B. I. Mohammed ◽  
Abdulaziz S. Alghamdi ◽  
Hassan M. Aljohani ◽  
Md. Moyazzem Hossain
Keyword(s):  
Negative Binomial ◽  
Real Data ◽  
Information Criterion ◽  
Mass Function ◽  
Bivariate Distribution ◽  
Statistical Properties ◽  
Model Parameters ◽  
Probability Mass Function ◽  
New Class ◽  
Probability Mass

This article proposes a novel class of bivariate distributions that are completely defined by stating their conditionals as Poisson exponential distributions. Numerous statistical properties of this distribution are also examined here, including the conditional probability mass function (PMF) and moments of the new class. The techniques of maximum likelihood and pseudolikelihood are used to estimate the model parameters. Additionally, the effectiveness of the bivariate Poisson exponential conditional (BPEC) distribution is compared to that of the bivariate Poisson conditional (BPC), the bivariate Poisson (BP), the bivariate Poisson–Lindley (BPL), and the bivariate negative binomial (BNB) distributions using a real-world dataset. The findings of Akaike information criterion (AIC) and Bayesian information criterion (BIC) reveal that the BPEC distribution performs better than the other distributions considered in this study. As a result, the authors claim that this distribution may be used to fit dependent and overspread count data.

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