• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.371-381
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• 2017

The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

• 한국초등수학교육학회지
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• 제24권1호
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• pp.1-30
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• 2020

본 연구는 통계적 소양 교육을 실천하기 위해 초등학교 통계교육의 주된 내용 요소에 해당하는 그래프 지도 중 특히 오류의 유형화에 주목하였다. 구체적으로 문헌 분석을 통해 통계적 문제해결의 관점에서 그래프의 교수학적 의의와 구성 요소를 확인하였고, 이를 표현하는 과정에서 나타나는 오류를 분류하여 각 사례들을 자료 분석 단계에서의 통계 윤리 문제와 연결하였다. 연구 결과, 그래프 오류 유형은 범주 표현에서의 오류, 빈도 표현에서의 오류, 맥락 제시에서의 오류로 분류할 수 있었고, 이러한 오류로 인해 자료 분석 단계에서 주관적인 분석 방법 채택, 시각적 착시현상 유도, 자료에 대한 정보 왜곡과 같은 통계 윤리 문제가 발생할 수 있음을 확인하였다. 그리고 우리나라 초등학교 수학과 교육과정에서는 오류를 범하지 않도록 정형화된 틀을 제공하고 그 틀에 맞춰 그래프를 그리는 절차에 주목하는 경향이 있었다. 이를 통해 그래프 오류 유형이 초등학교 통계교육에 제공하는 시사점을 통계적 소양 교육, 통계 윤리, 교사 지식의 관점에서 제시하였다.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.315-324
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• 2002

For estimating the error variance under the relative squared error loss in two-way analysis of variance models, we provide a class of hierarchical Bayes estimators and then derive a subclass of the hierarchical Bayes estimators, each member of which dominates the best multiple of the error sum of squares which is known to be minimax. We also identify a subclass of non-minimax hierarchical Bayes estimators.

• Journal of Preventive Medicine and Public Health
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• 제40권2호
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.333-344
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• 2012

We consider some statistical properties of the first order difference-based error variance estimator in nonparametric regression models with a single outlier. So far under an outlier(s) such difference-based estimators has been rarely discussed. We propose the first order difference-based estimator using the leave-one-out method to detect a single outlier and simulate the outlier detection in a nonparametric regression model with the single outlier. Moreover, the outlier detection works well. The results are promising even in nonparametric regression models with many outliers using some difference based estimators.

• Journal of the Korean Statistical Society
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• 제29권1호
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• pp.63-80
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• 2000

We consider the panel data regression model with nested error componets. In this paper, the several Lagrange Multipler tests for the nested error component model are derived. These tests extend the earlier work of Honda(1985), Moulton and Randolph(1989), Baltagi, et al.(1992) and King and Wu(1997) to the nested error component case. Monte Carlo experiments are conducted to study the performance of these LM tests.

• Communications for Statistical Applications and Methods
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• 제6권2호
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• pp.487-500
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• 1999

We propose a class of hierarchical Bayes estimators of the error variance under the relative squared error loss in balanced fixed-effects two-way analysis of variance models. Also we provide analytic expressions for the risk improvement of the hierarchical Bayes estimators over multiples of the error sum of squares. Using these expressions we identify a subclass of the hierarchical Bayes estimators each member of which dominates the best multiple of the error sum of squares which is known to be minimax. Numerical values of the percentage risk improvement are given in some special cases.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• Journal of the Korean Statistical Society
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• 제23권1호
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• pp.115-134
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• 1994

Polynomial errors-in-variables model with one predictor variable and one response variable is defined and an estimator of model is derived following the Booth's linear model estimation procedure. Since polynomial model is nonlinear function of the unknown regression coefficients and error-free predictors, it is nonlinear model in errors-in-variables model. As a result of applying linear model estimation method to nonlinear model, some additional assumptions are necessary. Hence, an estimator is derived under the assumption that the error variances are decrasing as sample size increases. Asymptotic propoerties of the derived estimator are provided. A simulation study is presented to compare the small sample properties of the derived estimator with those of OLS estimator.

• 한국임상보건과학회지
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• 제2권3호
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• pp.203-208
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• 2014

Purpose. To analysis the refractive error in 7-9 year-old Korea children. Methods. From July 2013 to June 2014, two hundred eighty two subjects were performed in refraction test using the Auto-Refractometry. Results. The refractive error by spherical equivalent among all subjects was myopia 47.58%, emmetropia 42.35%, astigmatism 32.33%, and hyperopia 8.76%. Myopia was more common in female than males although the difference was not statically significant. The axis of astigmatism was with the rule in 65%, against the rule in 31.5%, and oblique in 3.5% There was a statistical significance between 7 year and 9 year of male in the spherical equivalent power(p=0.010). Also there was a statistical significance between 7 years and 9 years of female in the spherical equivalent power(p=0.036). However, there was not a statistical significance between male and female in spherical equivalent power(p>0.5). Conclusions. In this study, myopia was the most common refractive error. On the other hand, The prevalence of the axis of astigmatism was the with- the- rule. The spherical equivalent of refractive error was similar results between male and female. However The refractive error was different style with aging. these data suggested that the analysis of the refractive error at young children can provide the information of useful diagnosis for the correction of visual acuity.