• 대한수학회보
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• 제43권1호
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• pp.213-223
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• 2006

In this paper we establish the Marcinkiewicz-Zygmund strong law of large numbers for blockwise adapted sequences. Some related results are considered.

• 대한수학회지
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• 제45권3호
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• pp.795-805
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• 2008

The aim of this paper is to extend the "classical degenerate convergence criterion" and the Feller weak law of large numbers to double adapted arrays of random variables.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2005년도 추계학술대회
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• pp.135-138
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• 2005

In this paper, we consider the problem of testing for parameter change in time series models based on a cusum of squares. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case was not discussed in literatures. Therefore, here we develop the cusum of squares type test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model. Simulation results are reported for illustration.

• 대한수학회지
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• 제45권1호
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• pp.289-300
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• 2008

For an array of dependent random variables satisfying a new notion of uniform integrability, weak laws of large numbers are obtained. Our results extend and sharpen the known results in the literature.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2001년도 추계학술발표회 논문집
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• pp.185-189
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• 2001

In this paper, we consider the problem of testing for parameter changes in time series models based on a sequential test. Although the test procedure is well-established for the mean and variance change, a general parameter case has not been discussed in the literature. Therefore, we develop a sequential test for parameter changes in a more general framework.

• 대한수학회논문집
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• 제16권2호
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• pp.291-296
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• 2001

For randomly indexed sums of the form (Equation. See Full-text), where {X(sub)ni, i$\geq$1, n$\geq$1} are random variables, {N(sub)n, n$\geq$1} are suitable conditional expectations and {b(sub)n, n$\geq$1} are positive constants, we establish a general weak law of large numbers. Our result improves that of Hong [3].

• Communications for Statistical Applications and Methods
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• 제31권4호
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• pp.427-440
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• 2024

The problem addressed is that of sequentially estimating the difference between the means of two populations with respect to the squared error loss, where each population distribution is a member of the one-parameter exponential family. A Bayesian approach is adopted in which the population means are estimated by the posterior means at each stage of the sampling process and the prior distributions are not specified but have twice continuously differentiable density functions. The main result determines an asymptotic second-order lower bound, as t → ∞, for the Bayes risk of a sequential procedure that takes M observations from the first population and t - M from the second population, where M is determined according to a sequential design, and t denotes the total number of observations sampled from both populations.

• 대한수학회논문집
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• 제21권4호
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• pp.779-786
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• 2006

Let $\mathbb{X}_t$ be an m-dimensional linear process defined by $\mathbb{X}_t=\sum{_{j=0}^\infty}\;A_j\;\mathbb{Z}_{t-j}$, t = 1, 2, $\ldots$, where $\mathbb{Z}_t$ is a sequence of m-dimensional random vectors with mean 0 : $m\times1$ and positive definite covariance matrix $\Gamma:m{\times}m$ and $\{A_j\}$ is a sequence of coefficient matrices. In this paper we give sufficient conditions so that $\sum{_{t=1}^{[ns]}\mathbb{X}_t$ (properly normalized) converges weakly to Wiener measure if the corresponding result for $\sum{_{t=1}^{[ns]}\mathbb{Z}_t$ is true.

• 대한수학회논문집
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• 제18권1호
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• pp.117-126
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• 2003

Let {$X_{nk}$\mid$1\;{\leq}\;k\;{\leq}\;n,\;n\;{\geq}\;1$} be an array of row negatively associated (NA) random variables which satisfy $P($\mid$X_{nk}$\mid$\;>\;x)\;{\leq}\;P($\mid$X$\mid$\;>\;x)$. For weighed sums ${{\Sigma}_{k=1}}^{Tn}\;a_kX_{nk}$ indexed by random variables {$T_n$\mid$n\;{\geq}$1$}, we establish a general weak law of large numbers (WLLN) of the form $({{\Sigma}_{k=1}}^{Tn}\;a_kX_{nk}\;-\;v_{[nk]})\;/b_{[an]}$ under some suitable conditions, where $\{a_n$\mid$n\;\geq\;1\},\; \{b_n$\mid$n\;\geq\;1\}$ are sequences of constants with $a_n\;>\;0,\;0\;<\;b_n\;\rightarrow \;\infty,\;n\;{\geq}\;1$, and {$v_{an}$\mid$n\;{\geq}\;1$} is an array of random variables, and the symbol [x] denotes the greatest integer in x.