• Title/Summary/Keyword: exponential distribution

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Goodness of Fit and Independence Tests for Major 8 Companies of Korean Stock Market (한국 주식시장 상위 8개사에 대한 적합도 검정 및 독립성 검정)

  • Min, Seungsik
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1245-1255
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    • 2015
  • In this paper, we investigated the major 8 companies of Korean stock market, and carried out the goodness of fit and independence tests. We found out the distributions of absolute returns are closed to compressed exponential distribution. The parameters are dominant that 1 < ${\beta}$ < 2, followed by ${\beta}=1$(exponential distribution) and ${\beta}=2$(normal distribution). Meanwhile, we assured that most of the absolute returns for major 8 companies have relevance to each other by chi-square independence test.

Comparison of Best Invariant Estimators with Best Unbiased Estimators in Location-scale Families

  • Seong-Kweon
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.275-283
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    • 1999
  • In order to estimate a parameter $(\alpha,\beta^r), r\epsilonN$, in a distribution belonging to a location-scale family we usually use best invariant estimator (BIE) and best unbiased estimator (BUE). But in some conditions Ryu (1996) showed that BIE is better than BUE. In this paper we calculate risks of BIE and BUE in a normal and an exponential distribution respectively and calculate a percentage risk improvement exponential distribution respectively and calculate a percentage risk improvement (PRI). We find the sample size n which make no significant differences between BIE and BUE in a normal distribution. And we show that BIE is always significantly better than BUE in an exponential distribution. Also simulation in a normal distribution is given to convince us of our result.

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Estimation of the exponential distribution based on multiply Type I hybrid censored sample

  • Lee, Kyeongjun;Sun, Hokeun;Cho, Youngseuk
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.3
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    • pp.633-641
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    • 2014
  • The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

Maximum Likelihood Estimation of Lifetime Distribution under Stress Bounded Ramp Tests: The Case Where Stress Loaded from Use Condition (스트레스 한계가 있는 램프시험하에서 신뢰수명분포의 최우추정: 사용조건에서부터 스트레스를 가하는 경우)

  • 전영록
    • Journal of Korean Society for Quality Management
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    • v.25 no.2
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    • pp.1-14
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    • 1997
  • This paper considers maximum likelihood (ML) estimation of lifetime distribution under stress bounded ramp tests in which the stress is increased linearly from used condition stress to the stress u, pp.r bound. The following assumptions are used: exponential lifetime distribution under a constant stress, an inverse power law relationship between stress and mean of exponential lifetime distribution, and a cumulative exposure model for the effect of changing stress. Likelihood equations for the parameters involved in the model and asymptotic distribution of the estimators are obtained, and a numerical example is given.

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CHARACTERIZATIONS OF THE EXPONENTIAL DISTRIBUTION BY RECORD VALUES

  • Chang, Se-Kyung;Lee, Min-Young
    • Journal of the Chungcheong Mathematical Society
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    • v.19 no.4
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    • pp.375-381
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    • 2006
  • This paper presents characterizations based on the identical distribution and the finite moments of the exponential distribution by record values. We prove that $X{\in}EXP({\sigma})$, ${\sigma}$>0, if and only if $X_{U(n+k)}-X_{U(n)}$ and $X_{U(n)}-X_{U(n-k)}$ for n > 1 and $k{\geq}1$ are identically distributed. Also, we show that $X{\in}EXP({\sigma})$, ${\sigma}$>0, if and only if $E(X_{U(n+k)}-X_{U(n)})=E(X_{U(n)}-X_{U(n-k)})$ for n>1 and $k{\geq}1$.

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On the comparison of cumulative hazard functions

  • Park, Sangun;Ha, Seung Ah
    • Communications for Statistical Applications and Methods
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    • v.26 no.6
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    • pp.623-633
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    • 2019
  • This paper proposes two distance measures between two cumulative hazard functions that can be obtained by comparing their difference and ratio, respectively. Then we estimate the measures and present goodness of t test statistics. Since the proposed test statistics are expressed in terms of the cumulative hazard functions, we can easily give more weights on earlier (or later) departures in cumulative hazards if we like to place an emphasis on earlier (or later) departures. We also show that these test statistics present comparable performances with other well-known test statistics based on the empirical distribution function for an exponential null distribution. The proposed test statistic is an omnibus test which is applicable to other lots of distributions than an exponential distribution.

The influence of the random censorship model on the estimation of the scale parameter of the exponential distribution (중도절단모형이 지수분포의 척도모수추정에 미치는 영향)

  • Kim, Namhyun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.393-402
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    • 2014
  • The simplest and the most important distribution in survival analysis is the exponential distribution. In this paper, we investigate the influence of the random censorship model on the estimation of the scale parameter of the exponential distribution. The considered random censorship models are Koziol-Green model and the generalized exponential distribution model. Two models have different meanings. Through the simulation study, the averages of the estimated values of the parameter do not show big differences, however the MSE of the estimator tends to be bigger when the supposed model is significantly different from the true model.

Empirical Bayes Test for the Exponential Parameter with Censored Data

  • Wang, Lichun
    • Communications for Statistical Applications and Methods
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    • v.15 no.2
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    • pp.213-228
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    • 2008
  • Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.

Estimation for a bivariate survival model based on exponential distributions with a location parameter

  • Hong, Yeon Woong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.921-929
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    • 2014
  • A bivariate exponential distribution with a location parameter is proposed as a model for a two-component shared load system with a guarantee time. Some statistical properties of the proposed model are investigated. The maximum likelihood estimators and uniformly minimum variance unbiased estimators of the parameters, mean time to failure, and the reliability function of system are obtained with unknown guarantee time. Simulation studies are given to illustrate the results.

Reference Priors for the Location Parameter in the Exponential Distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.19 no.4
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    • pp.1409-1418
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    • 2008
  • In this paper, we develop the reference priors for the common location parameter in two parameter exponential distributions. We derive the reference priors and prove the propriety of joint posterior distribution under the general prior including the reference priors. Through the simulation study, we show that the proposed reference prior matches the target coverage probabilities in a frequentist sense.

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