• 한국국방경영분석학회지
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• 제27권2호
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• pp.124-133
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• 2001

The purpose of this study is investigate the differences among parametric and nonparametric test statistics for the tree alternative hypothesis in the randomized block design. As the results, it was found that there was no large differences among parametric and nonparametric test statistics in power when the block sizes were larger, and Hollander's statistic had better power than other nonparametric test statistics. It is recommended that Hollander's test statistic is more useful method when we have no information about the distribution of population.

• Water Engineering Research
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• 제1권1호
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• pp.49-61
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• 2000

Magnitude-frequency relationships are used in the design of dams, highway bridges, culverts, water supply systems, and flood control structures. In this paper, possible techniques for analyzing flood frequency at a site are presented. A currently used approach to flood frequency analysis is based on the concept of parametric statistical inference. In this analysis, the assumption is make that the distribution function describing flood data in known. However, such an assumption is not always justified. Even though many people have shown that the nonparametric method provides a better fit to the data than the parometric method and gives more reliable flood estimates. the noparpmetric method implies a small probability in extrapolation beyond the highest observed data in the sample. Therefore, a remedy is presented in this paper by introducing an estimator which mixes parametric and nonparametric density estimate.

• 환경영향평가
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• 제4권2호
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• pp.93-103
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• 1995

This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

• Communications for Statistical Applications and Methods
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• 제19권5호
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• pp.721-729
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• 2012

Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.

• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.193-211
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• 2012

This paper deals with robust nonparametric regression analysis when the regressors are functional random fields. More precisely, we consider $Z_i=(X_i,Y_i)$, $i{\in}\mathbb{N}^N$ be a $\mathcal{F}{\times}\mathbb{R}$-valued measurable strictly stationary spatial process, where $\mathcal{F}$ is a semi-metric space and we study the spatial interaction of $X_i$ and $Y_i$ via the robust estimation for the regression function. We propose a family of robust nonparametric estimators for regression function based on the kernel method. The main result of this work is the establishment of the asymptotic normality of these estimators, under some general mixing and small ball probability conditions.

• 한국IT서비스학회지
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• 제16권4호
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• pp.1-13
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• 2017

This study examines how specific technology from Information and Communications Technology (ICT)-which plays a critical role in increasing productivity by promoting a spread of technology across the society though the use of big data, mobile or wearable devices-impacts of the productivity of society and productivity of added values, respectively. The impact of technology was studied from the perspective of efficiency levels of input. In order to provide an analysis, we have categorized ICT into 16 specific technologies and have set the number of companies and number of employees each as an input factor while setting the respective output and the output of added values as an output factor. Afterwards, we have applied data envelopment analysis (DEA) which is a form of nonparametric frontier analysis and measured the productivity and efficiency of added values for each technology. According to the analysis results, there were 2 technologies by the CRS standards, and 3 technologies by the VRS standards that showed relative efficiency levels. We have also presented some efficiency improvement strategies for specific technologies that revealed relative inefficiency and offered a reference set and projection point. In addition, we provide an analysis on scale efficiencies (SE), diminishing returns to scale (DRS), and increasing returns to scale (IRS) of each ICT.

• 응용통계연구
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• 제30권3호
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• pp.427-439
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• 2017

공변량(covariate)이 존재하는 경우, 각 처리군 간 효과의 차이를 검정하기 위한 대표적인 비모수적 방법에는 Quade (1967)가 제안한 검정법이 있다. 또한 반응변수에 대해 공변량으로 단순선형회귀분석을 실시하여 얻은 잔차에 대해 일원배치분산분석과 Kruskal Wallis가 제안한 방법을 적용하는 방법, 그리고 Hwang과 Kim (2012)이 제안한 비모수적 도구인 위치(placement)를 이용한 방법이 있다. 본 논문에서는 공분산분석 모형에서 Hwang과 Kim (2012)이 제안한 방법을 확장하여 공분산분석에서의 새로운 방법을 제안하였다. 또한 모의실험(Monte Carlo simulation study)을 통하여 기존의 검정법들과 제안한 방법의 검정력을 비교하였다.

• KSTLE International Journal
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• 제2권1호
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2129-2147
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• 2019

This paper introduces an adaptive face recognition method based on a Novel Incremental Kernel Nonparametric Discriminant Analysis (IKNDA) that is able to learn through time. More precisely, the IKNDA has the advantage of incrementally reducing data dimension, in a discriminative manner, as new samples are added asynchronously. Thus, it handles dynamic and large data in a better way. In order to perform face recognition effectively, we combine the Gabor features and the ordinal measures to extract the facial features that are coded across local parts, as visual primitives. The variegated ordinal measures are extraught from Gabor filtering responses. Then, the histogram of these primitives, across a variety of facial zones, is intermingled to procure a feature vector. This latter's dimension is slimmed down using PCA. Finally, the latter is treated as a facial vector input for the advanced IKNDA. A comparative evaluation of the IKNDA is performed for face recognition, besides, for other classification endeavors, in a decontextualized evaluation schemes. In such a scheme, we compare the IKNDA model to some relevant state-of-the-art incremental and batch discriminant models. Experimental results show that the IKNDA outperforms these discriminant models and is better tool to improve face recognition performance.

• 응용통계연구
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• 제31권3호
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• pp.343-352
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• 2018

설명변수가 주어졌을 때 반응변수의 평균적인 추세뿐만 아니라 극단적인 지역에서의 추세에 대해서 추정하고 싶거나 반응변수 분포의 일반적인 탐색을 위해서는 분위수 회귀분석과 평률 회귀분석을 사용할 수 있다. 본 논문에서는 평률 회귀모형의 추정을 위한 모수적 방법과 비모수적 방법의 성능을 비교하고자 한다. 이를 위해 각 추정 방법을 소개하고 여러 상황의 모의실험 및 실제자료에의 적용을 통해 비교 분석을 실시하였다. 모형에 따라 성능 차이가 있는데 자료의 형태가 복잡하여 변수 간의 관계를 유추하기 힘들 경우 비모수적으로 추정한 평률 회귀분석모형이 더욱 좋은 결과를 보였다. 일반적인 회귀분석의 경우와 달리 평률의 경우 후보가 되는 모수 모형을 상정하기 어렵다는 측면에서 볼 때, 비모수적 방법의 사용이 추천될 수 있다.