• 제목/요약/키워드: Non-parametric statistical analysis

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한의학 연구에 활용된 통계분석 방법에 대한 고찰 (A Review of Statistical Analysis Methods Applied on Traditional Korean Medicine Research)

  • 장선일;윤용갑;최경호
    • 대한한의학방제학회지
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    • 제17권1호
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    • pp.75-83
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    • 2009
  • Objective : The purpose of this study is to indicate of problems in statistical analysis method of "The Korean Journal of oriental Medical Prescription" and we will be proposed the useful application of the statistical analysis method. Methods : In this paper, we were analysed statistical analysis methodology from published journal articles "The Korean Journal of Oriental Medical Prescription" December, year 2000 to December, year 2008. We were investigated of problems in application of structured analysis methods those journal articles that including statistical analysis techniques and analysis methods. Results : 1. A random allocation of the experimental group and control groups are important factors in the planning process of statistical analysis. However, there are less explanation those journal articles. 2. There are no consideration in specimen size that there will be considerate by the level of significance and statistical test. 3. Many article authors were confused between parametric methods and non-parametric methods that they were applied parametric statistical analysis methods although inapplicable sample size. 4. There were applied the parametric methods consists of t-test instead non-parametric methods in the comparison of average intergroup relations. 5. There were less understanding posterior analysis and were confused with t-test. Conclusion : Our goal was to outline the key methods with a brief discussion of problems(statistical analysis methods), avenues for solutions. we recommend authors to use an appropriate statistical analysis methods for obtaining a more cautions results.

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Note on response dimension reduction for multivariate regression

  • Yoo, Jae Keun
    • Communications for Statistical Applications and Methods
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    • 제26권5호
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    • pp.519-526
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    • 2019
  • Response dimension reduction in a sufficient dimension reduction (SDR) context has been widely ignored until Yoo and Cook (Computational Statistics and Data Analysis, 53, 334-343, 2008) founded theories for it and developed an estimation approach. Recent research in SDR shows that a semi-parametric approach can outperform conventional non-parametric SDR methods. Yoo (Statistics: A Journal of Theoretical and Applied Statistics, 52, 409-425, 2018) developed a semi-parametric approach for response reduction in Yoo and Cook (2008) context, and Yoo (Journal of the Korean Statistical Society, 2019) completes the semi-parametric approach by proposing an unstructured method. This paper theoretically discusses and provides insightful remarks on three versions of semi-parametric approaches that can be useful for statistical practitioners. It is also possible to avoid numerical instability by presenting the results for an orthogonal transformation of the response variables.

How are Bayesian and Non-Parametric Methods Doing a Great Job in RNA-Seq Differential Expression Analysis? : A Review

  • Oh, Sunghee
    • Communications for Statistical Applications and Methods
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    • 제22권2호
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    • pp.181-199
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    • 2015
  • In a short history, RNA-seq data have established a revolutionary tool to directly decode various scenarios occurring on whole genome-wide expression profiles in regards with differential expression at gene, transcript, isoform, and exon specific quantification, genetic and genomic mutations, and etc. RNA-seq technique has been rapidly replacing arrays with seq-based platform experimental settings by revealing a couple of advantages such as identification of alternative splicing and allelic specific expression. The remarkable characteristics of high-throughput large-scale expression profile in RNA-seq are lied on expression levels of read counts, structure of correlated samples and genes, larger number of genes compared to sample size, different sampling rates, inevitable systematic RNA-seq biases, and etc. In this study, we will comprehensively review how robust Bayesian and non-parametric methods have a better performance than classical statistical approaches by explicitly incorporating such intrinsic RNA-seq specific features with flexible and more appropriate assumptions and distributions in practice.

수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 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.

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주성분 분석기법을 적용한 사면 계측데이터 평가 (Slope Displacement Data Estimation using Principal Component Analysis)

  • 정수정;김용수;안상로
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2010년도 춘계 학술발표회
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    • pp.1358-1365
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    • 2010
  • Estimating condition of slope is difficult because of nonlinear time dependency and seasonal effects, which affect the displacements. Displacements and displacement patterns of landslides are highly variable in time and space, and a unique approach cannot be defined to model landslide movements. Characteristics of movements are obtained by using a statistical method called Principal Component Analysis(PCA). The PCA is a non-parametric method to separate unknown, statistically uncorrelated source processes from observed mixed processes. In the non-parametric approaches, no physical assumptions of target systems are required. Instead, since the "best" mathematical relationship is estimated for given data sets of the input and output measured from target systems. As a consequence, non-parametric approaches are advantageous in modeling systems whose geomechanical properties are unknown or difficult to be measured. Non-parametric approaches are consequently more flexible in modeling than parametric approaches. This method is expected to be a useful tool for the slope management of and alarm systems.

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모수와 비모수 모형을 활용한 사망률 예측 비교 연구 (A study comparison of mortality projection using parametric and non-parametric model)

  • 김순영;오진호
    • 응용통계연구
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    • 제30권5호
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    • pp.701-717
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    • 2017
  • 급속한 고령화로 인하여 미래의 인구와 인구구조에 관해 사회와 정부의 관심이 증가하고 있으며 우리나라의 사망률은 감소하고 있으나 감소폭은 변동적이다. 본 연구에서는 이를 고려할 수 있는 모형을 살펴보고자 LC 모형, LM 모형, BMS 모형 그리고 비모수평활 기법이 적용된 FDM과 Coherent FDM을 비교 분석하여 연령별 사망률과 기대수명 예측의 정확성 측면에서 남녀 사망률 개선 추이를 예측하는데 적합한 모형을 살펴보았다. 또한 우리나라 사망률 예측에 비모수 기법의 활용 가능성을 검토하였다. 분석 결과 최근 자료의 추세를 잘 반영하는 비모수기법을 활용한 인구통계모델인 FDM과 Coherent FDM의 예측력이 우수함을 알 수 있었다. 결과적으로 FDM과 Coherent FDM은 적합이 뛰어나고, 미래에 변화가 크지 않다면 예측력 또한 우수하다 볼 수 있을 것이다.

야전 운용자료를 이용한 비 모수 통계 기반의 신뢰도 분석 기법 및 활용 방안 연구 (A Research of the Reliability Analysis and Application Method Based on Non-parametric Statistics Using Field Data)

  • 나일용
    • 한국군사과학기술학회지
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    • 제13권4호
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    • pp.594-600
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    • 2010
  • In this paper, we introduced non-parametric statisticals method that could analyse the field data and proposed application ways such as repair-part demand forcasting, MTBF estimation and trend analysis, identity comparison with two populations using the analytical results. In addition, we applied that to real field data which has been collected for about ten years from K series tracked vehicle. After that, we compared the results with those using traditional parametric statistical method, and verified the usability of them.

수질변화의 계량화를 위한 비모수적 통계 준거에 관한 연구 (A Study of Non-parametric Statistical Tests to Quantify the Change of Water Quality)

  • 이상훈
    • 환경영향평가
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    • 제6권1호
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    • pp.111-119
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    • 1997
  • This study was carried out to suggest the best statistical test which may be used to quantify the change of water quality between two groups. Traditional t-test may not be used in cases where the normality of underlying population distribution is not assured. Three non-parametric tests which are based on the relative order of the measurements, were studied to find out the applicability in water quality data analysis. The sign test is based on the sign of the deviation of the measurement from the median value, and the binomial distribution table is used. The signed rank test utilizes not only the sign but also the magnitude of the deviation. The Wilcoxon rank-sum test which is basically same as Mann-Whitney test, tests the mean difference between two independent samples which may have missing data. Among the three non-parametric tests studied, the singed rank test was found out to be applicable in the quantification of the change of water quality between two samples.

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Efficiency of Aggregate Data in Non-linear Regression

  • Huh, Jib
    • Communications for Statistical Applications and Methods
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    • 제8권2호
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    • pp.327-336
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    • 2001
  • This work concerns estimating a regression function, which is not linear, using aggregate data. In much of the empirical research, data are aggregated for various reasons before statistical analysis. In a traditional parametric approach, a linear estimation of the non-linear function with aggregate data can result in unstable estimators of the parameters. More serious consequence is the bias in the estimation of the non-linear function. The approach we employ is the kernel regression smoothing. We describe the conditions when the aggregate data can be used to estimate the regression function efficiently. Numerical examples will illustrate our findings.

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Practical statistics in pain research

  • Kim, Tae Kyun
    • The Korean Journal of Pain
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    • 제30권4호
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    • pp.243-249
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    • 2017
  • Pain is subjective, while statistics related to pain research are objective. This review was written to help researchers involved in pain research make statistical decisions. The main issues are related with the level of scales that are often used in pain research, the choice of statistical methods between parametric or nonparametric statistics, and problems which arise from repeated measurements. In the field of pain research, parametric statistics used to be applied in an erroneous way. This is closely related with the scales of data and repeated measurements. The level of scales includes nominal, ordinal, interval, and ratio scales. The level of scales affects the choice of statistics between parametric or non-parametric methods. In the field of pain research, the most frequently used pain assessment scale is the ordinal scale, which would include the visual analogue scale (VAS). There used to be another view, however, which considered the VAS to be an interval or ratio scale, so that the usage of parametric statistics would be accepted practically in some cases. Repeated measurements of the same subjects always complicates statistics. It means that measurements inevitably have correlations between each other, and would preclude the application of one-way ANOVA in which independence between the measurements is necessary. Repeated measures of ANOVA (RMANOVA), however, would permit the comparison between the correlated measurements as long as the condition of sphericity assumption is satisfied. Conclusively, parametric statistical methods should be used only when the assumptions of parametric statistics, such as normality and sphericity, are established.