• Title/Summary/Keyword: Methods: statistical

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STATISTICS PRESENT, NEAR FUTURE, AND BEYOND

  • Johnson, Richard A.
    • Communications for Statistical Applications and Methods
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    • v.8
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    • pp.5-12
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    • 2001
  • We berlin with a brief review of some important advances made in statistical theory over the last decade. The choice of topics is decidedly influenced by personal interests. Based on this review, we then propose some possible scenarios about the future of statistics.

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Estimation of slope , βusing the Sequential Slope in Simple Linear Regression Model

  • Choi, Yong;Kim, Dongjae
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.257-266
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    • 2003
  • Distribution-free estimation methods are proposed for slope, $\beta$ in the simple linear regression model. In this paper, we suggest the point estimators using the sequential slope based on sign test and Wilcoxon signed rank test. Also confidence intervals are presented for each estimation methods. Monte Carlo simulation study is carried out to compare the efficiency of these methods with least square method and Theil´s method. Some properties for the proposed methods are discussed.

The Choice of a Primary Resolution and Basis Functions in Wavelet Series for Random or Irregular Design Points Using Bayesian Methods

  • Park, Chun-Gun
    • Communications for Statistical Applications and Methods
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    • v.15 no.3
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    • pp.379-386
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    • 2008
  • In this paper, the choice of a primary resolution and wavelet basis functions are introduced under random or irregular design points of which the sample size is free of a power of two. Most wavelet methods have used the number of the points as the primary resolution. However, it turns out that a proper primary resolution is much affected by the shape of an unknown function. The proposed methods are illustrated by some simulations.

Analysis of the Statistical Methods used in Scientific Research published in The Korean Journal of Culinary Research (한국조리학회지에 게재된 학술적 연구의 통계적 기법 분석)

  • Rha, Young-Ah;Na, Tae-Kyun
    • Culinary science and hospitality research
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    • v.21 no.6
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    • pp.49-62
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    • 2015
  • Give that statistical analysis is an essential component of foodservice-related research, the purpose of this review is to analyse research trends of statistical methods applied to foodservice-related research. To achieve these objective, this study carried out a content analysis on a total of 251 out of 415 research articles published in The Korean Journal of Culinary Research(TKJCR) from January 2010 to December 2013. Of the total 164 research articles focussing on natural science research, qualitative research, articles written in English were excluded from the scope of this study. The results of this study are as follows. First, it turned out that 269 research articles applied quantitative research methods, and only 10 articles applied qualitative research methods among the 279 research articles based on social science research methods. Second, 20 article (8.0%) among the 251 did not specify the statistical methods or computer programs that were used for statistical analysis. Third, it was found that 228 articles (90.8%) used the SPSS program for data analysis. Fourth, in terms of frequency of use, it was revealed frequency analysis was most used, followed in order by reliability analysis, exploratory factor analysis, correlation analysis, regression analysis, structural equation modeling, confirmatory factor analysis, t-test, variance analysis, and cross tabs analysis, However, 3 out of 56 research articles that used a t-test did not suggest a t-value. 10 out of 64 articles that used ANOVA and demonstrated a significant difference in between-group mean did not conducted post-hoc test. Therefore, the researchers with interest in foodservice fields need to keep in mind that choosing and applying the correct statistical technique both determine the value and the success or failure of a study. To enhance the value and success of a study, it is necessary to use the proper statistical technique in an efficient way in order to prevent statistical errors.

A System for Medical Statistical Analysis Using Guide Maps and Interactive Visualization (가이드 맵과 인터랙티브 시각화를 이용한 의료 통계분석 시스템)

  • Lee Don-Soo;Choi Soo-Mi
    • Journal of Korea Multimedia Society
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    • v.8 no.7
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    • pp.1000-1011
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    • 2005
  • This paper presents a system for medical statistical analysis that helps medical professionals analyze clinical data more easily and accurately. It is able to recommend proper methods according to the distribution of sample data, and provides guide maps composed of icons for the understanding of the process of analysis. Besides general statistical analysis, it includes commonly-used statistical methods for medical fields, such as survival analysis and methods for repetitive measurements. The results of analysis are interactively displayed by 3D glyph-based visualization with uncertainty.

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Statistical Representation Methods of Ground Data (지반조사 데이터의 통계처리기법)

  • Lee, Kyu-Hwan;Yoon, Gil-Lim
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.10a
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    • pp.85-110
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    • 2008
  • Ground investigation data to be used as a basis for geotechnical analysis and foundation design are usually troubled with large uncertainty, due to natural variability and limited number of data. Statistical methods can be a rational tool for handling such uncertain ground data, in particular with a view to the selection of characteristic values for estimating ground design parameters used in design. The characteristic values of soil properties for use in geotechnical design have oftenly based on not only a subjective judgment but also engineer's past acumulated experience. This paper discussed some statistical methods which can handle such intrinsic ground uncertainty data with a case design in a rational manner.

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A computational note on maximum likelihood estimation in random effects panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.315-323
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    • 2019
  • Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

Fast Hough Transform Using Multi-statistical Methods (다중 통계기법을 이용한 고속 하프변환)

  • Cho, Bo-Ho;Jung, Sung-Hwan
    • Journal of Korea Multimedia Society
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    • v.19 no.10
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    • pp.1747-1758
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    • 2016
  • In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

Calibration by Median Regression

  • Jinsan Yang;Lee, Seung-Ho
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.265-277
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    • 1999
  • Classical and inverse estimation methods are two well known methods in statistical calibration problems. When there are outliers, both methods have large MSE's and could not estimate the input value correctly. We suggest median calibration estimation based on the LD-statistics. To investigate the robust performances, the influence function of the median calibration estimator is calculated and compared with other methods. When there are outliers in the response variables, the influence function is found to be bounded. In simulation studies, the MSE's for each calibration methods are compared. The estimated inputs as well as the performance of the influence functions are calculated.

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