• Title/Summary/Keyword: statistical theory

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Minimum Variance Unbiased Estimation for the Maximum Entropy of the Transformed Inverse Gaussian Random Variable by Y=X-1/2

  • Choi, Byung-Jin
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.657-667
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    • 2006
  • The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by $Y=X^{-1/2}$. The properties of the derived UMVU estimator is investigated.

Robust Inference for Testing Order-Restricted Inference

  • Kang, Moon-Su
    • The Korean Journal of Applied Statistics
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    • v.22 no.5
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    • pp.1097-1102
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    • 2009
  • Classification of subjects with unknown distribution in small sample size setup may involve order-restricted constraints in multivariate parameter setups. Those problems makes optimality of conventional likelihood ratio based statistical inferences not feasible. Fortunately, Roy (1953) introduced union-intersection principle(UIP) which provides an alternative avenue. Redescending M-estimator along with that principle yields a considerably appropriate robust testing procedure. Furthermore, conditionally distribution-free test based upon exact permutation theory is used to generate p-values, even in small sample. Applications of this method are illustrated in simulated data and read data example (Lobenhofer et al., 2002)

On a Skew-t Distribution

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.867-873
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    • 2001
  • In this paper we propose a family of skew- f distributions. The family is derived by a scale mixtures of skew-normal distributions introduced by Azzalini (1985) and Henze (1986). The salient features of the family are mathematical tractability and strict inclusion of the normal law. Further it includes a shape parameter, to some extent, controls the index of skewness. Necessary theory involved in deriving the family of distributions is provided and main properties of the family are also studied.

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A Bayesian Test Criterion for the Behrens-Firsher Problem

  • Kim, Hea-Jung
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.193-205
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    • 1999
  • An approximate Bayes criterion for Behrens-Fisher problem (testing equality of means of two normal populations with unequal variances) is proposed and examined. Development of the criterion involves derivation of approximate Bayes factor using the imaginary training sample approachintroduced by Spiegelhalter and Smith (1982). The proposed criterion is designed to develop a Bayesian test criterion having a closed form, so that it provides an alternative test to those based upon asymptotic sampling theory (such as Welch's t test). For the suggested Bayes criterion, numerical study gives comparisons with a couple of asymptotic classical test criteria.

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A Bayesian Approach to Finite Population Sampling Using the Concept of Pivotal Quantity

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.647-654
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    • 2003
  • Bayesian probability models for finite populations are considered assuming so-called the super-population. We find the posterior distribution of population mean by a new approach, using the concept of pivotal quantity for the small sample case. A large sample theory is also treated throught the concept of asymptotically pivotal quantity.

Hypothesis Testing for New Scores in a Linear Model

  • Park, Young-Hun
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.1007-1015
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    • 2003
  • In this paper we introduced a new score generating function for the rank dispersion function in a general linear model. Based on the new score function, we derived the null asymptotic theory of the rank-based hypothesis testing in a linear model. In essence we showed that several rank test statistics, which are primarily focused on our new score generating function and new dispersion function, are mainly distribution free and asymptotically converges to a chi-square distribution.

Waiting Times in Polling Systems with Markov-Modulated Poisson Process Arrival

  • Kim, D. W.;W. Ryu;K. P. Jun;Park, B. U.;H. D. Bae
    • Journal of the Korean Statistical Society
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    • v.26 no.3
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    • pp.355-363
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    • 1997
  • In queueing theory, polling systems have been widely studied as a way of serving several stations in cyclic order. In this paper we consider Markov-modulated Poisson process which is useful for approximating a superposition of heterogeneous arrivals. We derive the mean waiting time of each station in a polling system where the arrival process is modeled by a Markov-modulated Poisson process.

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Constrained Optimality of an M/G/1 Queueing System

  • Kim, Dong-Jin
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.203-206
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    • 2003
  • This paper studies constrained optimization of an M/G/1 queue with a server that can be switched on and off. One criterion is an average number of customers in the system and another criterion is an average operating cost per unit time, where operating costs consist of switching and running costs. With the help of queueing theory, we solve the problems of optimization of one of these criteria under a constraint for another one.

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Least Squares Approach for Structural Reanalysis

  • Kyung-Joon Cha;Ho-Jong Jang;Dal-Sun Yoon
    • Journal of the Korean Statistical Society
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    • v.25 no.3
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    • pp.369-379
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    • 1996
  • A study is made of approximate technique for structural reanalysis based on the force method. Perturbntion analysis of generalized least squares problem is adopted to reanalyze a damaged structure, and related results are presented.

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On the Conditionally Independent and Positive and Negative Dependence of Bivariate Stochastic Processes

  • Baek, Jong Il;Han, Kwang Hee
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.367-379
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    • 2002
  • We introduce a new concept of $\theta$ conditionally independent and positive and negative dependence of bivariate stochastic processes and their corresponding hitting times. We have further extended this theory to stronger conditions of dependence similar to those in the literature of positive and negative dependence and developed theorems which relate these conditions. Finally we are given some examples to illustrate these concepts.