• Title/Summary/Keyword: Distribution Journal

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Predictions for Progressively Type-II Censored Failure Times from the Half Triangle Distribution

  • Seo, Jung-In;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.21 no.1
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    • pp.93-103
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    • 2014
  • This paper deals with the problem of predicting censored data in a half triangle distribution with an unknown parameter based on progressively Type-II censored samples. We derive maximum likelihood predictors and some approximate maximum likelihood predictors of censored failure times in a progressively Type-II censoring scheme. In addition, we construct the shortest-length predictive intervals for censored failure times. Finally, Monte Carlo simulations are used to assess the validity of the proposed methods.

ON LOCALLY 𝜙-CONFORMALLY SYMMETRIC ALMOST KENMOTSU MANIFOLDS WITH NULLITY DISTRIBUTIONS

  • De, Uday Chand;Mandal, Krishanu
    • Communications of the Korean Mathematical Society
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    • v.32 no.2
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    • pp.401-416
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    • 2017
  • The aim of this paper is to investigate locally ${\phi}-conformally$ symmetric almost Kenmotsu manifolds with its characteristic vector field ${\xi}$ belonging to some nullity distributions. Also, we give an example of a 5-dimensional almost Kenmotsu manifold such that ${\xi}$ belongs to the $(k,\;{\mu})^{\prime}$-nullity distribution and $h^{\prime}{\neq}0$.

A note on the distance distribution paradigm for Mosaab-metric to process segmented genomes of influenza virus

  • Daoud, Mosaab
    • Genomics & Informatics
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    • v.18 no.1
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    • pp.7.1-7.7
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    • 2020
  • In this paper, we present few technical notes about the distance distribution paradigm for Mosaab-metric using 1, 2, and 3 grams feature extraction techniques to analyze composite data points in high dimensional feature spaces. This technical analysis will help the specialist in bioinformatics and biotechnology to deeply explore the biodiversity of influenza virus genome as a composite data point. Various technical examples are presented in this paper, in addition, the integrated statistical learning pipeline to process segmented genomes of influenza virus is illustrated as sequential-parallel computational pipeline.

Estimation for the Triangular Distribution under Progressive Type-II Censoring

  • Kang, Suk-Bok;Han, Jun-Tae;Jung, Won-Tae
    • Communications for Statistical Applications and Methods
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    • v.15 no.5
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    • pp.765-774
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    • 2008
  • In this paper, we derive the approximate maximum likelihood estimators(AMLEs) and maximum likelihood estimator of the scale parameter in a triangular distribution based on progressive Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation for various progressive censoring schemes.

Researches on the Potential Rises on the Neutral Line in Three Phase, Four-Wire Distribution Line Systems (공통중성선 3상4선식 배전선로의 중성선 전위상승에 관한 연구)

  • Park, Young-Moon
    • 전기의세계
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    • v.18 no.6
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    • pp.23-32
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    • 1969
  • The thesis has derived the formulas and computational algorithms useful for predicting and constraining the potential rises on the neutral line in 3-phase, 4-wire distribution line systems in the case of contact faults and single-line grounding faults. In addition it has suggested economically optimal designing conditions herewith of the distribution line systems in conduction with the potential restraining cost functions.

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A Closed-Form Bayesian Inferences for Multinomial Randomized Response Model

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.121-131
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    • 2007
  • In this paper, we examine the problem of estimating the sensitive characteristics and behaviors in a multinomial randomized response model using Bayesian approach. We derived a posterior distribution for parameter of interest for multinomial randomized response model. Based on the posterior distribution, we also calculated a credible intervals and mean squared error (MSE). We finally compare the maximum likelihood estimator and the Bayes estimator in terms of MSE.

Fluid Queueing Model with Fractional Brownian Input

  • Lee, Jiyeon
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.649-663
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    • 2002
  • We consider an unlimited fluid queueing model which has Fractional Brownian motion(FBM) as an input and a single server of constant service rate. By using the result of Duffield and O'Connell(6), we investigate the asymptotic tail-distribution of the stationary work-load. When there are multiple homogeneous FBM inputs, the workload distribution is similar to that of the queue with one FBM input; whereas for the heterogeneous sources the asymptotic work-load distributions is dominated by the source with the largest Hurst parameter.

AMLEs for the Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang Suk-Bok;Lee Sang-Ki
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.603-613
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    • 2005
  • We propose some estimators of the location parameter and derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter in the exponential distribution based on multiply Type-II censored samples. We calculate the moments for the proposed estimators of the location parameter, and the AMLEs which are the linear functions of the order statistics. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

Minimizing Weighted Mean of Inefficiency for Robust Designs

  • Seo, Han-Son
    • Communications for Statistical Applications and Methods
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    • v.15 no.1
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    • pp.95-104
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    • 2008
  • This paper addresses issues of robustness in Bayesian optimal design. We may have difficulty applying Bayesian optimal design principles because of the uncertainty of prior distribution. When there are several plausible prior distributions and the efficiency of a design depends on the unknown prior distribution, robustness with respect to misspecification of prior distribution is required. We suggest a new optimal design criterion which has relatively high efficiencies across the class of plausible prior distributions. The criterion is applied to the problem of estimating the turning point of a quadratic regression, and both analytic and numerical results are shown to demonstrate its robustness.