• Title/Summary/Keyword: Order Statistics

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Estimation in Autoregressive Process with Non-negative Innovations (양(陽)의 오차(誤差)를 가지는 백기회귀모형(白己回歸模型)에서의 추정(推定))

  • Lee, Kwang-Ho;Park, Jeong-Gun
    • Journal of the Korean Data and Information Science Society
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    • v.3 no.1
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    • pp.65-78
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    • 1992
  • In this paper, we obtain the natural estimators of the coefficient parameters and propose strongly consistent estimators of the parameter in the autoregressive model of order three with non-negative innovations. It is shown that the natural estimators are also strongly consistent for the parameters. We also compare the proposed estimators with the natural estimators and the least square estimators via Monte Carlo simulation studies.

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Estimation for Exponential Distribution Based on Multiply Type-II Censored Samples

  • Kang, Suk-Bok
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.203-210
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    • 2004
  • When the available sample is multiply Type-II censored, the maximum likelihood estimators of the location and the scale parameters of two- parameter exponential distribution do not admit explicitly. In this case, we propose some estimators which are linear functions of the order statistics and also propose some estimators by approximating the likelihood equations appropriately. We compare the proposed estimators by the mean squared errors.

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A Unit Root Test Based on Bootstrapping

  • Shin, Key-Il;Kang, Hee-Jeong
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.257-265
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    • 1996
  • We consider nonstationary autoregressive autoregressive process with infinite variance of error. In the case of infinite cariance, the limiting distribution of the estimated coefficient is different from that under the finite cariance assumption. In this paper we show that the bootstrap method can be used to approximate the distribution of ordinary least squares estimator of the coefficient in the first order random walk process with infinite variance through some empirical studies and we suggest a test procedure based on bootstrap method for the unit root test.

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INFERENCE FOR PEAKEDNESS ORDERING BETWEEN TWO DISTRIBUTIONS

  • Oh, Myong-Sik
    • Journal of the Korean Statistical Society
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    • v.33 no.3
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    • pp.303-312
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    • 2004
  • The concept of dispersion is intrinsic to the theory and practice of statistics. A formulation of the concept of dispersion can be obtained by comparing the probability of intervals centered about a location parameter. This is the peakedness ordering introduced first by Birnbaum (1948). We consider statistical inference concerning peakedness ordering between two arbitrary distributions. We propose non parametric maximum likelihood estimators of two distributions under peakedness ordering and a likelihood ratio test for equality of dispersion in the sense of peakedness ordering.

Estimation of the Mean and Variance for Normal Distributions whose Both Sides are Truncated

  • Hong, Chong-Sun;Choi, Yun-Young
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.249-259
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    • 2002
  • In order to estimate the mean and variance for a Normal distribution which is truncated at both right and left sides, maximum likelihood estimators based on the entire sample from the original distribution are compared with the sample mean and variance of the censored sample which is the data remaining after truncation using simulation. We found that, surprisingly, the mean squared error of the mean based on the censored data Is smaller than that of the full sample estimators.

Edgeworth Expansion and Bootstrap Approximation for Survival Function Under Koziol-Green Model

  • Kil Ho;Seong Hwa
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.233-244
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    • 2000
  • Confidence intervals for survival function give useful information about the lifetime distribution. In this paper we develop Edgeworkth expansions as approximation to the true and bootstrap distributions of normalized nonparametric maximum likelihood estimator of survival function in the Koziol-Green model and then use these results to show that the bootstrap approximations have second order accuracy.

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SOME GENERALIZED GAMMA DISTRIBUTION

  • Nadarajah Saralees;Gupta Arjun K.
    • Journal of the Korean Statistical Society
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    • v.36 no.1
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    • pp.93-109
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    • 2007
  • Gamma distributions are some of the most popular models for hydrological processes. In this paper, a very flexible family which contains the gamma distribution as a particular case is introduced. Evidence of flexibility is shown by examining the shape of its pdf and the associated hazard rate function. A comprehensive treatment of the mathematical properties is provided by deriving expressions for the nth moment, moment generating function, characteristic function, Renyi entropy and the asymptotic distribution of the extreme order statistics. Estimation and simulation issues are also considered. Finally, a detailed application to drought data from the State of Nebraska is illustrated.

A Class of Discrete Time Coverage Growth Functions for Software Reliability Engineering

  • Park, Joong-Yang;Lee, Gye-Min;Park, Jae-Heung
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.497-506
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    • 2007
  • Coverage-based NHPP SRGMs have been introduced in order to incorporate the coverage growth behavior into the NHPP SRGMs. The coverage growth function representing the coverage growth behavior during testing is thus an essential factor of the coverage-based NHPP SRGMs. This paper proposes a class of discrete time coverage growth functions and illustrates its application to real data sets.

Virtual Coverage: A New Approach to Coverage-Based Software Reliability Engineering

  • Park, Joong-Yang;Lee, Gyemin
    • Communications for Statistical Applications and Methods
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    • v.20 no.6
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    • pp.467-474
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    • 2013
  • It is common to measure multiple coverage metrics during software testing. Software reliability growth models and coverage growth functions have been applied to each coverage metric to evaluate software reliability; however, analysis results for the individual coverage metrics may conflict with each other. This paper proposes the virtual coverage metric of a normalized first principal component in order to avoid conflicting cases. The use of the virtual coverage metric causes a negligible loss of information.

A Refinement of Point Forecast Using Dependency Structure in Irregualr Component of BOK-X12-ARIMA

  • Hwang, S.Y.;Yang, S.K.
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.141-147
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    • 2006
  • BOK-X12-ARIMA has been developed by the Bank of Korea in order to accomodate special features such as lunar effect, labor day and election effect which are intrinsic in Korean seasonal time series. Irregular component resulting from BOK-X12-ARIMA is usually treated as white noise time series. If this shows dependency structure, it may be advisable to incorporate dependency in irregular component into prediction. This article illustrates how to refine point forecast using dependency structure in irregular component.

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