• Title/Summary/Keyword: 통계적 추정

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Analysis of Textbooks on Statistical Problem-Solving Process and Statistical Literacy (통계적 문제해결과정 및 통계적 소양에 관한 <확률과 통계> 교과서 분석)

  • Lee, Jiyeon;Rim, Haemee
    • Journal of the Korean School Mathematics Society
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    • v.24 no.2
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    • pp.191-216
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    • 2021
  • This study analyzes how statistical literacy is implemented along with the statistical problem-solving process as described in the Statistical Estimation Unit of the textbook by the 2015 revised mathematics curriculum. The analytical framework was developed from the literature, and consists of 'context', 'variability', 'mathematical and statistical knowledge', 'using of technological instruments', 'critical attitude', and 'communication'. From the perspective of the statistical problem-solving process, the analysis revealed that many tasks equivalent to 'Analyzing Data' but lacked tasks related to 'Interpreting Results' and 'Formulating Questions'. As a result of analyzing the reflection of each element of statistical literacy, 'mathematical and statistical knowledge' was the most common task, but 'critical attitude' and 'using of technological instruments' were rarely dealt with. Based on the results of this textbook analysis, it was intended to provide implications for improving the curriculum and the development of textbooks for the growth of statistical literacy.

A Study on the Method of Building 3D GIS Database Using the Statistical Estimating Methods of Well Log for Balancing Seismic Data (탄성파 자료 보정용 검층 기록의 통계적 추정방법을 이용한 3차원 GIS DB 구축방법에 관한 연구)

  • Um, Jong-Seok
    • Journal of Korea Spatial Information System Society
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    • v.5 no.1 s.9
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    • pp.39-47
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    • 2003
  • The purpose of this paper is to present the method of acquiring 3D GIS data using the statistical estimating methods of Well Log for balancing Seismic data. We use the reflection coefficients of seismic data to get the parameters for the reservoir characterization and we balance the reflection coefficients of seismic data using well log to increase the confidence of the estimated result. Well logs are required to balance the reflection coefficients at the point where seismic data are acquired. In this research, we discuss the geostatistical estimation methods and we applied these methods to real data. Kriging gives high weights to the close well logs, which means estimated results are mainly affected by close well log. High value of cross variograms gave big difference on cokriging result comparing to kriging results and low value of cross variogram gave little differences.

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On Rice Estimator in Simple Regression Models with Outliers (이상치가 존재하는 단순회귀모형에서 Rice 추정량에 관해서)

  • Park, Chun Gun
    • The Korean Journal of Applied Statistics
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    • v.26 no.3
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    • pp.511-520
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    • 2013
  • Detection outliers and robust estimators are crucial in regression models with outliers. In such studies the focus is on detecting outliers and estimating the coefficients using leave-one-out. Our study introduces Rice estimator which is an error variance estimator without estimating the coefficients. In particular, we study a comparison of the statistical properties for Rice estimator with and without outliers in simple regression models.

Comparison Study on the Performances of NLL and GMM for Estimating Diffusion Processes (NLL과 GMM을 중심으로 한 확산모형 추정법 비교)

  • Kim, Dae-Gyun;Lee, Yoon-Dong
    • The Korean Journal of Applied Statistics
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    • v.24 no.6
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    • pp.1007-1020
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    • 2011
  • Since the research of Black and Scholes (1973), modeling methods using diffusion processes have performed principal roles in financial engineering. In modern financial theories, various types of diffusion processes were suggested and applied in real situations. An estimation of the model parameters is an indispensible step to analyze financial data using diffusion process models. Many estimation methods were suggested and their properties were investigated. This paper reviews the statistical properties of the, Euler approximation method, New Local Linearization(NLL) method, and Generalized Methods of Moment(GMM) that are known as the most practical methods. From the simulation study, we found the NLL and Euler methods performed better than GMM. GMM is frequently used to estimate the parameters because of its simplicity; however this paper shows the performance of GMM is poorer than the Euler approximation method or the NLL method that are even simpler than GMM. This paper shows the performance of the GMM is extremely poor especially when the parameters in diffusion coefficient are to be estimated.

The Method to Estimate Saliency Values using Gauss Weight (가우스 가중치를 이용한 돌출 값 추정을 위한 방법)

  • Yu, Young-Jung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.4
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    • pp.965-970
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    • 2013
  • It is important work to extract saliency regions from an image as preprocessing for various image processing methods. In this paper, we introduce an improved method to estimate saliency value of each pixel from an image. The proposed method is an improved work of the previously studied method using color and statistical framework to estimate saliency values. At first, saliency value of each pixel is calculated using the local contrast of an image region at various scales and the most significant saliency pixel is determined using saliency value of each pixel. Then, saliency value of each pixel is again estimated using gauss weight with respect to the most significant saliency pixel and the saliency of each pixel is determined to calculate initial probability. At last, the saliency value of each pixel is calculated by Bayes' rule. The experiments show that our approach outperforms the current statistical based method.

Statistical Properties of Business Survey Index (기업경기실사지수의 통계적 성질 고찰)

  • Kim, Kyu-Seong
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.263-274
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    • 2010
  • Business survey index(BSI) is an economic forecasting index made on the basis of the past achievement of the company and enterpriser's plan and decision for the future. Even the index is very popular in economic situations, only a little research result is known to the public. In the paper we investigate statistical properties of BSI. We define population BSI in the finite population and estimate it unbiasedly. Also we derive the variance of the estimated BSI and its unbiased estimator. In addition, confidence interval of the estimated BSI is proposed. We asserte that confidence interval of the estimated BSI is more reasonable than the relative standard error.

Optimal Network Design for the Estimation of Areal Rainfall (면적강우량 산정을 위한 관측망 최적설계 연구)

  • Lee, Jae-Hyeong;Yu, Yang-Gyu
    • Journal of Korea Water Resources Association
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    • v.35 no.2
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    • pp.187-194
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    • 2002
  • To improve the accuracy of the areal rainfall estimates over a river basin, the optimal design method of rainfall network was studied using the stochastic characteristics of measured rainfall data. The objective function was constructed with the estimation error of areal rainfall and observation cost of point rainfall and the observation sites with minimum objective function value were selected as the optimal network. As a stochastic variance estimator, kriging model was selected to minimize the error terms. The annual operation cost including the installation cost was considered as the cost terms and an accuracy equivalent parameter was used to combine the error and cost terms. The optimal design method of rainfall network was studied in the Yongdam dam basin whose raingauge numbers need to be enlarged for the optimal rainfall networks of the basin.

Statistical Timing Analysis of Partially-Depleted SOI Gates (부분 공핍형 SOI 게이트의 통계적 타이밍 분석)

  • Kim, Kyung-Ki
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.44 no.12
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    • pp.31-36
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    • 2007
  • This paper presents a novel statistical characterization for accurate timing analysis in Partially-Depleted Silicon-On-Insulator (PD-SOI) circuits in BSIMSOI3.2 100nm technology. The proposed timing estimate algorithm is implemented in Matlab, Hspice, and C, and it is applied to ISCAS85 benchmarks. The results show that the error is within 5% compared with Monte Carlo simulation results.