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Journal of the Korean Statistical Society

The Korean Statistical Society

  • Quarterly
  • /
  • 1226-3192(pISSN)
  • /
  • 2005-2863(eISSN)

Domain

  • Mathematics ＞ Models/Data analysis

Aim & Scope

The Journal of the Korean Statistical Society publishes research articles that make original contributions to the theory and methodology of statistics and probability. It also welcomes papers on innovative applications of statistical methodology, as well as papers that give an overview of current topic of statistical research with judgements about promising directions for future work. The journal welcomes contributions from all countries.

http://ees.elsevier.com/jkss/ KSCI SCOPUS

Volume 25 Issue 2

  1. Kim, Yoon-Tae 161
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    When we deal with a Hilbert space-valued Stochastic Differential Equation (SDE) (or Stochastic Partial Differential Equation (SPDE)), depending on some unknown parameters, the solution usually has a Fourier series expansion. In this situation we consider the maximum likelihood method for the statistical estimation problem and derive the asymptotic properties (consistency and normality) of the Maximum Likelihood Estimator (MLE).
  2. Hong, Dug-Hun 175
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    Let $S_n,n$ = 1, 2,... denote the partial sums of not necessarily in-dependent random variables. Let N(c) = min${ n ; S_n > c}$, c $\geq$ 0. Theorem 2 states that N (c), (suitably normalized), tends to 0 in p-mean, 1 $\leq$ p < 2, as c longrightarrow $\infty$ under mild conditions, which generalizes earlier result by Gut(1974). The proof follows by applying Theorem 1, which generalizes the known result $E$\mid$S_n$\mid$^p$ = o(n), 0 < p< 2, as n .rarw..inf. to randomly indexed partial sums.
  3. Cho, Dae-Hyeon 185
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    In this paper we consider the gambler's ruin problem with N players and derive the formula for computing the expected ruin time when the initial fortunes of all N players are the same. And we present an example for the case of N = 5.
  4. Kee-Won Lee;Songyong Sim 195
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    A bootstrap method is used to correct the apparent downward bias of a naive plug-in bootstrap model selection criterion, which is shown to enjoy a high degree of accuracy. Comparison of bootstrap method with the asymptotic method is made through an illustrative example.
  5. Woochul Kim;Duk-Hyun Ko;Keewon Lee 205
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    The bootstrap calibration method for empirical likelihood is considered to make a confidence region for the regression coefficients. Asymptotic properties are studied regarding the coverage probability. Small sample simulation results reveal that the bootstrap calibration works quite well.
  6. Kim, Woochul;Park, Byeong U. 217
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    This paper gives a rigorous proof of an asymptotic result about bias and variance for a transformation-based nonparametric regression estimator proposed by Park et al (1995).
  7. Lee, Sang-Yeol;Kim, Young-Won 235
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    The ordinary least squares estimator of the disturbance variance in the linear regression model with stationary errors is shown to be asymptotically unbiased when the error process has a spectral density bounded from the above and away from zero. Such error processes cover a broad class of stationary processes, including ARMA processes.
  8. Tae-Sung Kim;Song-Ho Kim 243
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    Let X and Y be random vectors in R$^{n}$ . A random vector X is 'more associated' than Y if and only if P(X $\in$ A ∩ B) - P(X $\in$ A)P(X $\in$ B) $\geq$ P(Y $\in$ A ∩ B)-P(Y $\in$ A)P(Y $\in$ B) for all open upper sets A and B. By requiring the above inequality to hold for some open upper sets A and B various notions of positive dependence orderings which are weaker than 'more associated' ordering are obtained. First a general theory is given and then the results are specialized to some concepts of a particular interest. Various properties and interrelationships are derived.
  9. Song-Ho Kim;Tae-Sung Kim 255
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    Let $(X_{1j}, X_{2j}, … , X_{nj}, Y_j/)$j = 1, 2, … , n, be a sample of size n on an (m + l)-dimensional vector $(X_1, X_2, … , X_m, Y)$, m .geq. 1. If $Y_{(r)}$ denote the rth order statistic from Y, then the $X_{[r:n]}$ paired with $Y_(r)$ is termed the concomitant vector of the order statistics. The general distributions of concomitant of order statistics will be found. The mean, variance and covariance of$X_{[r:n]}$ Will be studied. Then we will apply the results to the multivariate normal variate case.e.
  10. Cho, Wan-Hyun;Park, Jeong-Soo 265
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    The nonparametric deconvolution problems are studied to recover an unknown density when the data are contaminated with Gaussian error. We propose the estimator which is a linear combination of kernel type estimates of derivertives of the observed density function. We show that this estimator is consistent and also consider the properties of estimator at small sample by simulation.
  11. Park, Dong-Kwon 277
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    The minimum aberration criterion is commonly used for selecting good fractional factorial designs. In this paper we give same necessary conditions for $3^{n-k}$ fractional factorial designs. We obtain minimum aberration $3^{n-k}$ designs for k = 2 and any n. For k > 2, minimum aberration designs have not found yet. As an alternative, we select a design with minimum aberration among minimum-variance designs.
  12. Kim, Hea-Jung 289
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    This paper suggests a new diagnostic measure for detecting influential observations in two group linear discriminant analysis(LDA). It is developed from an information theoretic point of view using the minimum discrimination information(MDI) methodology. MDI estimator of symmetric divergence by Kullback(l967) is taken as a measure of the power of discrimination in LDA. It is shown that the effect of an observation over the power of discrimination is fully explained by the diagnostic measure. Asymptotic distribution of the proposed measure is derived as a function of independent chi-squared and standard normal variables. By means of the distributions, a couple of methods are suggested for detecting the influential observations in LDA. Performance of the suggested methods are examined through a simulation study.