• Journal of the Korean Mathematical Society
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• v.58 no.6
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• pp.1347-1365
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• 2021

For µ = (µ₁, …, µ_t) (µ_j > 0), ξ = (z₁, …, z_t, w) ∈ ℂ^n₁ × … × ℂ^n_t × ℂ^m, define $${\Omega}({\mu},t)=\{{\xi}{\in}\mathbb{B}_{n_1}{\times}{\cdots}{\times}\mathbb{B}_{n_t}{\times}\mathbb{C}^m:{\parallel}w{\parallel}^2 where $\mathbb{B}_{n_j}$ is the unit ball in ℂ^n_j (1 ≤ j ≤ t), C(χ, µ) is a constant only depending on χ = (n₁, …, n_t) and µ = (µ₁, …, µ_t), which is a special type of generalized Cartan-Hartogs domain. We will give some sufficient and necessary conditions for the boundedness of some type of operators on L^p(Ω(µ, t), ω) (the weighted L^p space of Ω(µ, t) with weight ω, 1 < p < ∞). This result generalizes the works from certain classes of generalized complex ellipsoids to the generalized Cartan-Hartogs domain Ω(µ, t).

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.463-473
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• 2001

선형모형의 회귀계수의 L$_1$-추정량의 점근분포는 오차항의 중앙값에 종속되어있는데, 이 값은 잔차의 순서통계량의 함수로 추정될 수 있다. 본 논문에서는 오차항 중앙값의 추정량을 유도하는 몇 가지 방법을 소개하고 몬테칼로 실험을 통하여 가장 바람직한 추정량의 형태를 제안하였다. 또한 제안한 추정량을 이용하면 검정문제에서도 좋은 결과를 얻을 수 있음을 보였다.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1311-1317
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• 2010

A continuous time asymmetric power GARCH(1,1) model is suggested, based on a single background driving L$\'{e}$vy process. The stochastic differential equation for the given process is derived and the strict stationarity and kth order moment conditions are examined.

• Communications for Statistical Applications and Methods
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• v.3 no.2
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• pp.299-307
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• 1996

This article is concerned with the algorithms for the least median of squares estimator. An algorithm based on the $L{\infty}$ .inf.-estimation procedure is proposed in an attempt to improve the optimality of the estimate. And it is shown that the proposed algorithm yields more optimal estimate than the traditional resampling algorithms. The proposed algorithm employs a linear scaling transformation at each iteration of the$L{\infty}$-algorithm to deal with its computational inefficiency problem.

• Journal of the Korean Statistical Society
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• v.20 no.2
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• pp.202-207
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• 1991

In Le Cam's earlier work on superefficiency, it is proved that if an estimate is superefficient at a given paramter value $\theta$$\_$0/, then there must exist an infinite sequence {$\theta$$\_$n/}) of values(conversing to $\theta$$\_$0/) at which this estimate is worse than M. L. E. for certain classes of loss functions. For one-dimensional cases, these classes of lass functions include squared error loss. However. for multi-dimensional cases, they do not. This note is to give an example where a superefficiest estimator of a multi-dimensional parameter is not inferior to M. L. E. along any sequence ($\theta$$\_$n/) converging to the point of superefficiency with respect to the squared error loss.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.41-51
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• 2022

We forecast the US oil consumption level taking advantage of google trends. The google trends are the search volumes of the specific search terms that people search on google. We focus on whether proper selection of google trend terms leads to an improvement in forecast performance for oil consumption. As the forecast models, we consider the least absolute shrinkage and selection operator (LASSO) regression and the structured regularization method for large vector autoregressive (VAR-L) model of Nicholson et al. (2017), which select automatically the google trend terms and the lags of the predictors. An out-of-sample forecast comparison reveals that reducing the high dimensional google trend data set to a low-dimensional data set by the LASSO and the VAR-L models produces better forecast performance for oil consumption compared to the frequently-used forecast models such as the autoregressive model, the autoregressive distributed lag model and the vector error correction model.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.37-53
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• 2024

In this study, flood records from 79 sites across Thailand were analyzed to estimate flood indices using the regional frequency analysis based on the L-moments method. Observation sites were grouped into homogeneous regions using k-means and Ward's clustering techniques. Among various distributions evaluated, the generalized extreme value distribution emerged as the most appropriate for certain regions. Regional growth curves were subsequently established for each delineated region. Furthermore, 20- and 100-year return values were derived to illustrate the recurrence intervals of maximum rainfall across Thailand. The predicted return values tend to increase at each site, which is associated with growth curves that could describe an increasing long-term predictive pattern. The findings of this study hold significant implications for water management strategies and the design of flood mitigation structures in the country.

• Journal of the Korean Statistical Society
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• v.22 no.2
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• pp.191-200
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• 1993

An asymptotic estimation problem of the unknown mean is studied under a general loss function. The proof of this result is based on the asymptotic expansion of the risk function. Also conditions for second order admissibility and minimaxity of a class of estimators depending only on the sample mean are established.

• Journal of Korean Society for Quality Management
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• v.13 no.2
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• pp.8-12
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• 1985

We study the Bayes estimation procedure of ${\theta}=P_r$=(Y < X) when the experiment is terminated before all of the items on the test have failed and the failed items are partially replaced. Comparisons with the M.L.E., M.V.U.E. and Bayes estimator are made through Monte Carlo simulation.

• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.1-12
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• 1995

Sample skewness has not received much attention from researchers to design a control chart. In this paper, control charts based on two skewness measures are studied to control a manufacturing process. One skewness measure is the third central moment about mean, the other is the third L-moment which is a linear combination of order statistics. Since the exact sampling distributions of two skewness measures are unknown, empirical sampling distributions are studied using simulation. The sampling distributions are used to design control charts for skewness and performance of two skewness measures is compared.