• Communications for Statistical Applications and Methods
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• v.22 no.6
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• pp.665-674
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• 2015

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.557-587
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• 2005

This paper elucidates the limiting Gaussian distribution of a class of rank order statistics {$T_N$} for two sample problem pertaining to empirical processes of the squared residuals from two independent samples of GARCH processes. A distinctive feature is that, unlike the residuals of ARMA processes, the asymptotics of {$T_N$} depend on those of GARCH volatility estimators. Based on the asymptotics of {$T_N$}, we empirically assess the relative asymptotic efficiency and effect of the GARCH specification for some GARCH residual distributions. In contrast with the independent, identically distributed or ARMA settings, these studies illuminate some interesting features of GARCH residuals.

• Journal of the Korean Statistical Society
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• v.28 no.3
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• pp.371-387
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• 1999

For possibly nonstationary autoregressive moving average, modeling based on the original observations rather than the differenced observations is considered. Under this scheme, sample autocorrelation functions, parameter estimates, model diagnostic statistics, and prediction are all computed from the original data instead of the differenced data. The methods and results established under stationarity of data are shown to naturally extend to the nonstationarity of one autoregressive unit root. The sample ACF and PACF can be used for ARMA order determination. The BIC order is strongly consistent. The parameter estimates are asymptotically normal. The portmanteau statistic has chi-square distribution. The predictor is asymptotically equivalent to that based on the differenced data.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.71-77
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• 1997

S independent sample 0,1,2, $\cdots$, s-1 (or stages 0,1,2, $\cdots$, s-1) are available from the Raleigh population. Procedure for predicting any order statistic in the $(s+1)^{th}$ sample is developed by obtaining the predictive distribution at stage s. Bounds for the sample size at stage S, in order to have the variance at stage S less than that at stage (s-1), are obtained.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.31-50
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• 1999

We revisit the problems of testing three-factor classifica-tion models with a single observation per cell. A common approach in analyzing such nonreplicated data is to omit the highest order in-teraction and regard it as error. This paper discusses the use of a multiplicative model(See and Smith 1996 and 1998) which is applied on residuals in order to separate the variablility due to three-factor interaction from what is counted as random error. in particualr to test the significance of the interaction term we derived an approxi-mated distribution of the likelihood ratio test statistic based on the quadrilinear model known as Tucher's three-mode principal compo-nent model. The derivation utilizes the distribution of the eignevalues of the Wishart matrix.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.395-406
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• 2003

In this thesis, we propose a test statistic for testing exponentiality against NBU alternatives. Our test statistics is based on a linear function of the order statistics and is readily applied in the case of small sample as well as large sample. The exact and asymptotic distribution of the test statistics is derived and asymptotic efficiencies are studied. Our new test is easier to compute and performs better for several alternatives than test of Hollander and Proschan(1972).

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.347-358
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• 1996

A new test for goodness-of-fit is presented. It is a modification of a test of LaRiccia (1991). These tests are applicable to continuous lo-cation/scale models. The new test statistic is based on a few selected order statistics taken from the sample, while the LaRiccia test is based directly on the full sample. Each test embeds the hypothesized model in a larger linear model and proceeds to test the goodness-of-fit hy-pothesis by testing the coefficients of this linear model appropriately. The general theory is presented. The tests are compared via computer simulation to a related test of Ali and Umbach (1989) for distributions that could be used as lifetime models. An important aspect of all these tests is that only standard $X_2$ tables are used. Selection of the spacings of the order statistics is discussed.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1309-1314
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• 2012

The SAMED filter is introduced as a wide class of multi-stage filters which encompass linear FIR and nonlinear order statistic filters. The output of SAMED filter is linear combination of sub-median outputs. In this paper, optimal SAMED filter is designed for images corrupted by various noise, and performance is analogized. The experimental result shows that the efficiency of each order of SAMED filters is depends on type of noise. It is shown that low order filters are effective in Gaussian environments but high order filters are effective in impulsive case. This result may be used to follow-up research on successive SAMED filters.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1381-1388
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• 2014

This paper is proposed a wavelet-based the order statistics MAD(Median Absolute Deviation) method of SAR(Synthetic Aperture Radar) image for image enhancement. also The method of compared and defined the threshold the wavelet coefficients using MAD of the wavelet coefficients of the detail subbands was proposed to effectively image enhancement. In order to complement the disadvantage, the threshold of the proposed method sets up the image statistic and excludes the distortion. The hardware design is used FPGA of Xilinx and DSP system for the image enhancement and compressed encoding of the proposed algorithm. Therefore the proposed method is totally verified by comparing with the several other images.

• Journal of Preventive Medicine and Public Health
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• v.43 no.1
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• pp.9-17
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• 2010

Objectives: Parkinson's disease is one of the most common neurodegenerative diseases in the elderly population. In order to estimate the prevalence of Parkinson's disease in the community, the application of a good screening tool is essential. We evaluated the validity and reliability of a Parkinson's disease screening questionnaire and propose an alternative measure to improve its validity for use in community surveys. Methods: We designed the study in a three-phase approach consisting of a screening questionnaire, neurologic examination, and confirmatory examination. A repeated survey was administered to patients with disease detected in the community and on 150 subjects. We examined internal consistency using Cronbach's alpha test, test-retest reliability using the kappa statistic, and validity using sensitivity, specificity, and ROC curves. Unadjusted odds ratios were utilized for the estimation of weights for each questionnaire item. Results: The Cronbach's alpha of the questionnaire was 0.708. The kappa statistic for test-retest reliability was good to generally fair in most of the items. When newly proposed weighting scores were used, the optimum cut-off value was 7/8. When cut-off value was 5/6 for surveying prevalence in a community, the sensitivity was 0.98, and the specificity was 0.61, with simultaneous improvement in reliability. Conclusions: We recommend 5/6 as the ideal cut-off value for the survey of PD prevalence in community. This questionnaire designed for the Korean community could help future epidemiologic studies of PD.