• Title/Summary/Keyword: correlation methods

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Study on Correlation between Difference of Pelvic Height and Gait Balance of Patients with Abnormal Postures (자세이상을 호소하는 환자의 골반 높이 차이와 보행 밸런스 관계에 대한 연구)

  • Park, Jung-Woo;Jeong, Su-Hyeon
    • Journal of Korean Medicine Rehabilitation
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    • v.24 no.3
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    • pp.149-155
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    • 2014
  • Objectives This study was designed to investigate the correlation between the difference of pelvic height and difference of gait balance. Methods 62 cases of patients who received treatment from January 2011 to March 2014 for abnormal postures were analyzed. Their difference of pelvic height were estimated by whole spine X-ray analysis and gait balance were estimated by Treadmill Gait Analysis system. The data were analyzed to find out correlation between difference of pelvic height and difference of gait balance, and correlation between the position of pelvic tilt and gait balance higher side. Pearson correlation and Chi-square analysis were used. Results Pelvic height heigher side were more left than right side, and gait balance higher side were also more left than right side. Difference of pelvic height and difference of gait balance had a positive linear relationship, but there was no significant correlation. The position of pelvic tilt had significant correlation with gait balance higher side. Conclusions The position of pelvic tilt had significant correlation with gait balance higher side and difference of pelvic height had no significant correlation with difference of gait balance.

Adaptive Video-Dissolve Detection Method Based on Correlation Between Two Scenes

  • Won, Jong-Un;Park, Jae-Gark;Chung, Yoon-su;Park, Kil-Houm
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1519-1522
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    • 2002
  • In this paper, we propose a new adaptive dissolve detection method based on the analysis of a dissolve modeling error that is the difference between an ideally modeled dissolve curve without any correlation and an actual variance curve with a correlation. The dissolve modeling error is determined based on a correlation between two scenes and variances for each scene. First, Candidate regions are extracted by using the characteristics of a parabola that is downward convex, then the candidate region will be verified based on a dissolve modeling error. If a dissolve modeling error on a candidate region is less than a threshold that is defined by a dissolve modeling error with a target correlation, the candidate region should be a dissolve region with a correlation less than the target correlation. The threshold is adaptively determined based on the variances between the candidate regions and the target correlation. By considering the correlation between neighbor scenes, the proposed method is able to be a semantic scene-change detector. The proposed algorithm was tested on various types of data and its performance proved to be more accurate and reliable when compared with other commonly used methods

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Minimax Eccentricity Estimation for Multiple Set Factor Analysis

  • Hyuncheol Kang;Kim, Keeyoung
    • Journal of the Korean Statistical Society
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    • v.31 no.2
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    • pp.163-175
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    • 2002
  • An extended version of the minimax eccentricity factor estimation for multiple set case is proposed. In addition, two more simple methods for multiple set factor analysis exploiting the concept of generalized canonical correlation analysis is suggested. Finally, a certain connection between the generalized canonical correlation analysis and the multiple set factor analysis is derived which helps us clarify the relationship.

Bayesian Hypothesis Testing for Intraclass Correlation Coefficient

  • Lee, Seung-A;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.551-566
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    • 2006
  • In this paper, we consider a Bayesian model selection for the intraclass correlation coefficient in familiar data. In particular, we compare two nested models such as the independence and intraclass models using the reference prior. A criterion for testing is the Bayesian Reference Criterion by Bernardo (1999) and the Intrinsic Bayes Factor by Berger and Pericchi (1996). We provide numerical examples using simulation data sets for illustration.

A Simple Geometric Approach to Evaluating a Bivariate Normal Orthant Probability

  • Lee, Kee-Won;Kim, Yoon-Tae;Kim, U-Jung
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.595-600
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    • 1999
  • We present a simple geometric approach which uses polar transformation and elementary trigonometry to evaluating an orthant probability in a bivariate normal distribution. Figures are provided to illustrate the situation for varying correlation coefficient. We derive the distribution of the sample correlation coefficient from a bivariate normal distribution when the sample size is 2 as an application.

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Regression and Correlation Analysis via Dynamic Graphs

  • Kang, Hee Mo;Sim, Songyong
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.695-705
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    • 2003
  • In this article, we propose a regression and correlation analysis via dynamic graphs and implement them in Java Web Start. For the polynomial relations between dependent and independent variables, dynamic graphics are implemented for both polynomial regression and spline estimates for an instant model selection. The results include basic statistics. They are available both as a web-based service and an application.

Improved Blind Multipath Estimation for Long Code DS-CDMA

  • Yu Qian;Bi Guoan;Zhang Gaonan
    • Journal of Communications and Networks
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    • v.7 no.3
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    • pp.278-283
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    • 2005
  • This paper proposes a blind channel estimation scheme for long code direct sequence code division multiple access (DS­CDMA) systems with multipath fading channels. This scheme combines the advantages of Toeplitz displacement and correlation matching methods to achieve improved performance. The basic idea is to remove the effects of noise and interferences with Toeplitz displacement operation and then estimate the multi path channel parameters with the correlation matching method. Simulation results are presented to show that the proposed scheme provides better MSE performance and robustness against the near-far problem.

Canonical Correlation Biplot

  • Park, Mi-Ra;Huh, Myung-Hoe
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.11-19
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    • 1996
  • Canonical correlation analysis is a multivariate technique for identifying and quantifying the statistical relationship between two sets of variables. Like most multivariate techniques, the main objective of canonical correlation analysis is to reduce the dimensionality of the dataset. It would be particularly useful if high dimensional data can be represented in a low dimensional space. In this study, we will construct statistical graphs for paired sets of multivariate data. Specifically, plots of the observations as well as the variables are proposed. We discuss the geometric interpretation and goodness-of-fit of the proposed plots. We also provide a numerical example.

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DIGITAL OPTION PRICING BASED ON COPULAS WITH STOCHASTIC SIMULATION

  • KIM, M.S.;KIM, SEKI
    • The Pure and Applied Mathematics
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    • v.22 no.3
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    • pp.299-313
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    • 2015
  • In this paper, we show the effectiveness of copulas by comparing the correlation of market data of year 2010 with those of years 2006-2009 and investigate copula functions as pricing methods of digital and rainbow options through real market data. We propose an accurate method of pricing rainbow options by using the correlation coefficients obtained from the copula functions depending on strike prices between assetes instead of simple traditional correlation coefficients.

CORRELATION COEFFICIENT OF GENERALIZED INTUITIONISTIC FUZZY SETS BY STATISTICAL METHOD

  • PARK, JIN HAN;PARK, YONG BEOM;LIM, KI MOON
    • Honam Mathematical Journal
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    • v.28 no.3
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    • pp.317-326
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    • 2006
  • Based on the geometrical representation of a generalized intuitionistic fuzzy set, we take into account all three parameters describing generalized intuitionistic fuzzy set and propose new methods to calculate the correlation coefficient for generalized intuitionistic fuzzy sets by means of mathematical statistics.

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