• Title/Summary/Keyword: Statistical Distribution

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Distribution Functions Describing the Microbiological Contamination of Seasoned Soybean Sprouts

  • Park, Jin-Pyo;Lee, Dong-Sun;Paik, Hyun-Dong
    • Food Science and Biotechnology
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    • v.17 no.3
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    • pp.659-663
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    • 2008
  • Different statistical distribution functions were examined to find an adequate distribution function to describe the microbial contamination behavior of a Korean side dish product, seasoned soybean sprouts for different seasons and market groups. The triang distribution was the best for any market groups in winter, while the logistic distribution could describe the microbial contamination in log CFU/g for all the market groups in spring and summer. From parametric bootstrapping based on the fitted distributions, it was found that a normal distribution could describe the distribution of mean microbial count in log CFU/g for all the seasons and market groups. Statistical parameters for each season/market group are presented to estimate the confidence interval.

Classical and Bayesian methods of estimation for power Lindley distribution with application to waiting time data

  • Sharma, Vikas Kumar;Singh, Sanjay Kumar;Singh, Umesh
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.193-209
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    • 2017
  • The power Lindley distribution with some of its properties is considered in this article. Maximum likelihood, least squares, maximum product spacings, and Bayes estimators are proposed to estimate all the unknown parameters of the power Lindley distribution. Lindley's approximation and Markov chain Monte Carlo techniques are utilized for Bayesian calculations since posterior distribution cannot be reduced to standard distribution. The performances of the proposed estimators are compared based on simulated samples. The waiting times of research articles to be accepted in statistical journals are fitted to the power Lindley distribution with other competing distributions. Chi-square statistic, Kolmogorov-Smirnov statistic, Akaike information criterion and Bayesian information criterion are used to access goodness-of-fit. It was found that the power Lindley distribution gives a better fit for the data than other distributions.

A comparison of inverse transform and composition methods of data simulation from the Lindley distribution

  • Okwuokenye, Macaulay;Peace, Karl E.
    • Communications for Statistical Applications and Methods
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    • v.23 no.6
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    • pp.517-529
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    • 2016
  • This study compares the inverse transform and the composition methods for generating data from the Lindley distribution. The expression for the inverse of the distribution function for the Lindley distribution does not exist in closed form. Hence, authors of many empirical studies on the Lindley distribution used methods for generating Lindley variates other than the inverse transform. We generated data from the Lindley distribution using the inverse transform approach by obtaining the Lindley variates numerically; we also generated data from this distribution using the composition approach. Following the generation of the Lindley variates using these two methods, we compare some statistical properties of the estimates of the Lindley model parameters based on the generated data. We conclude that the two methods produce similar results.

Some Exponentiated Distributions

  • Ali, M. Masoom;Pal, Manisha;Woo, Jung-Soo
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.93-109
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    • 2007
  • In this paper we study a number of new exponentiated distributions. The survival function, failure rate and moments of the distributions have been derived using certain special functions. The behavior of the failure rate has also been studied.

A Study on the Posterior Density under the Bayes-empirical Bayes Models

  • Sohn, Joong-K.Sohn;Kim, Heon-Joo-Kim
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.215-223
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    • 1996
  • By using Tukey's generalized lambda distribution, appoximate posterior density is derived under the Bayes-empirical Bayes model. The sensitivity of posterior distribution to the hyperprior distribution is examined by using Tukey's generalized lambda distriburion which approximate many well-knmown distributions. Based upon Monte Varlo simulation studies it can be said that posterior distribution is sensitive to the cariance of the prior distribution and to the symmetry of the hyperprior distribution. Also posterior distribution is approximately obtained by using the following methods : Lindley method, Laplace method and Gibbs sampler method.

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On Two-Piece Double Exponential Distribution

  • Lingappaiah, G.S.
    • Journal of the Korean Statistical Society
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    • v.17 no.1
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    • pp.46-55
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    • 1988
  • Two-piece double exponential distribution (TPDE) with one piece $(X \leq 0)$ having the scale parameter $\theta_1$ while the other piece (X>0) having $\theta_2$ is considered here. Distribution of the sum of n-independent variables from such a distribution is obtained. Special cases of this distribution are also treated. Next, distribution of the ratio of two independent (TPDE) variables is derived. As an extension, distribution of $x_1/x_2x_3$ is expressed terms of hypergeometric functions. A small table gives the power of the test regarding double exponential against (TPDE).

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Generalized half-logistic Poisson distributions

  • Muhammad, Mustapha
    • Communications for Statistical Applications and Methods
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    • v.24 no.4
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    • pp.353-365
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    • 2017
  • In this article, we proposed a new three-parameter distribution called generalized half-logistic Poisson distribution with a failure rate function that can be increasing, decreasing or upside-down bathtub-shaped depending on its parameters. The new model extends the half-logistic Poisson distribution and has exponentiated half-logistic as its limiting distribution. A comprehensive mathematical and statistical treatment of the new distribution is provided. We provide an explicit expression for the $r^{th}$ moment, moment generating function, Shannon entropy and $R{\acute{e}}nyi$ entropy. The model parameter estimation was conducted via a maximum likelihood method; in addition, the existence and uniqueness of maximum likelihood estimations are analyzed under potential conditions. Finally, an application of the new distribution to a real dataset shows the flexibility and potentiality of the proposed distribution.

Effects of Calibration Rounds on the Statistical Distribution of Muzzle Velocity in Acceptance Test of Propelling Charge (추진장약 수락시험시 포구속도 확률분포에 기준탄이 미치는 영향)

  • Park, Sung-Ho;Kim, Jae-Hoon
    • Journal of the Korea Institute of Military Science and Technology
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    • v.17 no.2
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    • pp.204-212
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    • 2014
  • The purpose of this paper is to investigate the effects of calibration rounds on the statistical distribution of the muzzle velocity in acceptance test of propelling charge. It is shown that the normal distribution fits best among statistical distributions from goodness-of fit test. The 3p-Weibull distribution is also acceptable because the shape of the probability density function curve is similar to that of normal distribution and it also has near zero skewness value. Muzzle velocities of test rounds uncompensated by calibration rounds showed high variation and had comparatively higher skewness. Because the skewness of normal distribution is defined to be zero, calibration rounds make the normality of data higher.

Implementation of Estimation and Inference on the Web

  • Kang, Heemo;Sim, Songyong
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.913-926
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    • 2000
  • An electronic statistics text on the web is implemented. The introduced text provide interactive instructions on the statistical estimation and inference. As a by-product, we also provide a calculation of quantiles and p-value of t-distribution and standard normal distribution. This program was written in JAVA programming language.

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Local Sensitivity Analysis using Divergence Measures under Weighted Distribution

  • Chung, Younshik;Dey, Dipak K.
    • Journal of the Korean Statistical Society
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    • v.30 no.3
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    • pp.467-480
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    • 2001
  • This paper considers the use of local $\phi$-divergence measures between posterior distributions under classes of perturbations in order to investigate the inherent robustness of certain classes. The smaller value of the limiting local $\phi$-divergence implies more robustness for the prior or the likelihood. We consider the cases when the likelihood comes form the class of weighted distribution. Two kinds of perturbations are considered for the local sensitivity analysis. In addition, some numerical examples are considered which provide measures of robustness.

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