• Title/Summary/Keyword: Empirical distribution

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ESTIMATION OF THE DISTRIBUTION FUNCTION FOR STATIONARY RANDOM FIELDS OF ASSOCIATED PROCESSES

  • Kim, Tae-Sung;Ko, Mi-Hwa;Yoo, Yeon-Sun
    • Communications of the Korean Mathematical Society
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    • v.19 no.1
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    • pp.169-177
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    • 2004
  • For a stationary field $\{X_{\b{j}},\b{j}{\;}\in{\;}{\mathbb{Z}}^d_{+}\}$ of associated random variables with distribution function $F(x)\;=\;P(X_{\b{1}}\;{\leq}\;x)$ we study strong consistency and asymptotic normality of the empirical distribution function, which is proposed as an estimator for F(x). We also consider strong consistency and asymptotic normality of the empirical survival function by applying these results.

On the Estimation of the Empirical Distribution Function for Negatively Associated Processes

  • Kim, Tae-Sung;Lee, Seung-Woo;Ko, Mi-Hwa
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.229-235
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    • 2001
  • Let {X$\_$n/, n$\geq$1] be a stationary sequence of negatively associated random variables with distribution function F(x)=P(X$_1$$\leq$x). The empirical distribution function F$\_$n/(x) based on X$_1$, X$_2$,....., X$\_$n/ is proposed as an estimator for F$\_$n/(x). Strong consistency and asymptotic normality of F$\_$n/(x) are studied. We also apply these ideas to estimation of the survival function.

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Bayesian and Empirical Bayesian Prediction Analysis for Future Observation

  • Jeong Hwan Ko
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.465-471
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    • 1997
  • This paper deals with the problems of obtaining some Bayesian and empirical Bayesian Predictive densities and prediction intervals of a future observation $X_{(\tau+\gamma)}$ in the Rayleigh distribution. Using an inverse gamma prior distribution, some prodictive densities and prodiction intervals are proposed and studied. Also the behaviors of the proposed results are examined via numerical examples.

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An Empirical Inquiry into Psychological Heuristics in the Context of the Korean Distribution Industry within the Stock Market

  • Jeong-Hwan LEE;Se-Jun LEE;Sam-Ho SON
    • Journal of Distribution Science
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    • v.21 no.9
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    • pp.103-114
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    • 2023
  • Purpose: This paper aims to assess psychological heuristics' effectiveness on cumulative returns after significant stock price changes. Specifically, it compares availability and anchoring heuristics' empirical validity due to conflicting stock return predictions. Research Design, Data, and Methodology: This paper analyzes stock price changes of Korean distribution industry stocks in the KOSPI market from January 2004 to July 2022, where daily fluctuations exceed 10%. It evaluates availability heuristics using daily KOSPI index changes and tests anchoring heuristics using 52-week high and low stock prices as reference points. Results: As a result of the empirical analysis, stock price reversals did not consistently appear alongside changes in the daily KOSPI index. By contrast, stock price drifts consistently appeared around the 52-week highest stock price and 52-week lowest stock price. The result of the multiple regression analysis which controlled for both company-specific and event-specific variables supported the anchoring heuristics. Conclusions: For stocks related to the Korean distribution industry in the KOSPI market, the anchoring heuristics theory provides a consistent explanation for stock returns after large-scale stock price fluctuations that initially appear to be random movements.

On scaled cumulative residual Kullback-Leibler information

  • Hwang, Insung;Park, Sangun
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1497-1501
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    • 2013
  • Cumulative residual Kullback-Leibler (CRKL) information is well defined on the empirical distribution function (EDF) and allows us to construct a EDF-based goodness of t test statistic. However, we need to consider a scaled CRKL because CRKL is not scale invariant. In this paper, we consider several criterions for estimating the scale parameter in the scale CRKL and compare the performances of the estimated CRKL in terms of both power and unbiasedness.

A Test of Multivariate Normality Oriented for Testing Elliptical Symmetry

  • Park, Cheol-Yong
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.221-231
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    • 2006
  • A chi-squared test of multivariate normality is suggested which is oriented for detecting deviations from elliptical symmetry. We derive the limiting distribution of the test statistic via a central limit theorem on empirical processes. A simulation study is conducted to study the accuracy of the limiting distribution in finite samples. Finally, we compare the power of our method with those of other popular tests of multivariate normality under a non-normal distribution.

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A Study on the Methodology of Distribution Study in Korea -basis on empirical analysis- (한국에서의 유통학문 연구 방법론에 대한 소고)

  • Youn, Myoung-kil;Kim, Yoo-oh
    • Journal of Distribution Science
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    • v.5 no.1
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    • pp.75-88
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    • 2007
  • The purpose of this dissertation is to provide foundation for methodology of distribution study. Furthermore, this study attempts to stimulate firm establishment of distribution study. Through this, development of domestic distribution industry could be expected alongside with distribution study. This dissertation designates problems of methodology that applied by some researchers then, attempts to discuss and approach with efforts. By this point, this research could be considering as inspirational, Thus further study required expending its boundary depth in continuation.

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Multivariate empirical distribution functions and descriptive methods (다변량 경험분포함수와 시각적인 표현방법)

  • Hong, Chong Sun;Park, Jun;Park, Yong Ho
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.1
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    • pp.87-98
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    • 2017
  • The multivaiate empirical distribution function (MEDF) is defined in this work. The MEDF's expectation and variance are derived and we have shown the MEDF converges to its real distribution function. Based on random samples from bivariate standard normal distribution with various correlation coefficients, we also obtain MEDFs and propose two kinds of graphical methods to visualize MEDFs on two dimensional plane. One is represented with at most n stairs with similar arguments as the step function, and the other is described with at most n curves which look like bivariate quantile vector. Even though these two descriptive methods could be expressed with three dimensional space, two dimensional representation is obtained with ease and it is enough to explain characteristics of bivariate distribution functions. Hence, it is possible to visualize trivariate empirical distribution functions with three dimensional quantile vectors. With bivariate and four variate illustrative examples, the proposed MEDFs descriptive plots are obtained and explored.

Weak Convergence of U-empirical Processes for Two Sample Case with Applications

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.31 no.1
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    • pp.109-120
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    • 2002
  • In this paper, we show the weak convergence of U-empirical processes for two sample problem. We use the result to show the asymptotic normality for the generalized dodges-Lehmann estimates with the Bahadur representation for quantifies of U-empirical distributions. Also we consider the asymptotic normality for the test statistics in a simple way.

Empirical Bayes Confidence Intervals of the Burr Type XII Failure Model

  • Choi, Dal-Woo
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.155-162
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    • 1999
  • This paper is concerned with the empirical Bayes estimation of one of the two shape parameters(${\theta}$) in the Burr(${\beta},\;{\theta}$) type XII failure model based on type-II censored data. We obtain the bootstrap empirical Bayes confidence intervals of ${\theta}$ by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive empirical Bayes confidence intervals through Monte Carlo study are also presented.

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