• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.307-324
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• 1993

The limiting distribution of the excess over the boundary is determined for the autoregressive process.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.1079-1082
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• 1999

This paper presents a denoising algorithm that can suppress additive noise components while preserving signal components in the wavelet domain. The algorithm uses the local statistics of wavelet coefficients to attenuate noise components adaptively. Then threshohding operation is followed to reject the residuary noise components in the wavelet coefficients. Simulations are carried out over 1-D signals corrupted by Gaussian noise and the experimental results show the effectiveness of the proposed algorithm.

• Journal of the Korean Statistical Society
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• 제22권1호
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• pp.27-37
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• 1993

Since the analytic expression for a diagnostic in the logistic regression model is not available, one-step estimation is often used by a case-deletion point of view. In this paper, infinitesimal perturbation approach is used, and it is shown that the scale transformation of infinitesimal perturbation approach is eventually equal to the weighted perturbation of local influence approach and the replacement measure. Also, multiple cases deletion for the masking effect is considered.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.213-217
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• 2012

Fuzzy k-means clustering is an attractive alternative to the ordinary k-means clustering in analyzing multivariate data. Fuzzy versions yield more natural output by allowing overlapped k groups. In this study, we modify a fuzzy k-means clustering algorithm to be used for undirected social networks, apply the algorithm to both real and simulated cases, and report the results.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.31-38
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• 2003

A simple method is proposed to detect the number of change points and test the location and size of multiple change points with jump discontinuities in an otherwise smooth regression model. The proposed estimators are based on a local linear regression fit by the comparison of left and right one-side kernel smoother. Our proposed methodology is explained and applied to real data and simulated data.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 춘계 학술발표회 논문집
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• pp.173-178
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• 2005

We derive an It${\hat{o}}$ formula for generalized functionals for the fractional Brownian sheet with arbitrary Hurst parameter ${H_1},\;H_2$ ${\epsilon}$ (0,1). As an application, we consider a stochastic integral representation for the local time of the fractional Brownian sheet.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.781-790
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• 1999

In this paper we consider estimation of cancer incidence rates for local areas. The raw estimates usually are based on small sample sizes and hence are usually unreliable. A hierarchical Bayes generalized linear model is used which connects the local areas thereby enabling one to 'borrow strength' Random effects with pairwise difference priors model the spatial structure in the data. The methods are applied to cancer incidence estimation for census tracts in a certain region of the state of New York.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.413-428
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.525-534
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.519-524
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• 2003

We suggest a method of identifying outliers, using local influence, in regression when linear constraints are imposed on the regression coefficients. An example is given for illustration.