• 제목/요약/키워드: Covariance pattern model

검색결과 22건 처리시간 0.018초

Inference on the Joint Center of Rotation by Covariance Pattern Models

  • Kim, Jinuk
    • 한국운동역학회지
    • /
    • 제28권2호
    • /
    • pp.127-134
    • /
    • 2018
  • Objective: In a statistical linear model estimating the center of rotation of a human hip joint, which is the parameter related to the mean of response vectors, assumptions of homoscedasticity and independence of position vectors measured repeatedly over time in the model result in an inefficient parameter. We, therefore, should take into account the variance-covariance structure of longitudinal responses. The purpose of this study was to estimate the efficient center of rotation vector of the hip joint by using covariance pattern models. Method: The covariance pattern models are used to model various kinds of covariance matrices of error vectors to take into account longitudinal data. The data acquired from functional motions to estimate hip joint center were applied to the models. Results: The results showed that the data were better fitted using various covariance pattern models than the general linear model assuming homoscedasticity and independence. Conclusion: The estimated joint centers of the covariance pattern models showed slight differences from those of the general linear model. The estimated standard errors of the joint center for covariance pattern models showed a large difference with those of the general linear model.

콜레스테롤 자료에 대한 적정 공분산행렬 형태 산출에 관한 통계적 분석 (A statistical analysis on the selection of the optimal covariance matrix pattern for the cholesterol data)

  • 조진남;백재욱
    • Journal of the Korean Data and Information Science Society
    • /
    • 제21권6호
    • /
    • pp.1263-1270
    • /
    • 2010
  • 60명의 환자들을 20명씩3개 그룹으로 나누어 각 그룹마다 다른 종류의 식이요법을 실시한 후 1주 간격으로 5주간에 걸쳐서 콜레스테롤 수치에 대한 반복측정 자료를 얻었다. 해당자료를 바탕으로 적합성여부와 유의성 검정을 실시한 결과 등분산 Toeplitz가 다양한 공분산행렬 형태들 중에서 가장 적합한 공분산구조 모형으로 판명되었다. 이 모형에서는 시점들 간의 상관계수는 0.64-0.78로 대체적으로 높은 상관관계들을 보여주고 있으며, 모수인자들의 유의성검정 결과, 시간효과는 대단히 유의하게 나타났으나, 처리 및 처리와 시간과의 교호작용효과는 유의하지 않은 것으로 판명되었다.

체중감량자료에 대한 적정 공분산형태모형 산출에 관한 실증연구 (An empirical study on the selection of the optimal covariance pattern model for the weight loss data)

  • 조진남
    • Journal of the Korean Data and Information Science Society
    • /
    • 제20권2호
    • /
    • pp.377-385
    • /
    • 2009
  • 서울시에 거주하는 25명의 여대생을 대상으로 식이요법에 대한 체중감량 효과를 비교하고자 식이요법과 운동을 병행하는 그룹과 식이요법만 실시하는 그룹으로 나누어서, 8주간에 걸쳐서 2주 간격으로 측정을 실시하여 각 그룹별로 4회 반복측정실험자료를 얻었다. 이 실험자료를 바탕으로 반복측정에 관한 혼합모형을 이용하여 분석한 결과 처리별 Toeplitz 공분산형태가 가장 적절한 모형으로 선택되었다. 처리별 Toeplitz 공분산형태를 가정하여 분석한 결과, 식이요법 이전의 체중값과 시간의 차이에 따른 효과는 대단히 유의하지만, 처리와 시간 간의 교호작용은 유의하지 않은 것으로 나타났으며, 식이요법과 운동을 병행한 그룹의 학생들이 식이요법만 섭취한 그룹의 학생들보다 좀더 효과적인 체중감량의 효과가 있었음이 판명되었다.

  • PDF

A Covariance-matching-based Model for Musical Symbol Recognition

  • Do, Luu-Ngoc;Yang, Hyung-Jeong;Kim, Soo-Hyung;Lee, Guee-Sang;Dinh, Cong Minh
    • 스마트미디어저널
    • /
    • 제7권2호
    • /
    • pp.23-33
    • /
    • 2018
  • A musical sheet is read by optical music recognition (OMR) systems that automatically recognize and reconstruct the read data to convert them into a machine-readable format such as XML so that the music can be played. This process, however, is very challenging due to the large variety of musical styles, symbol notation, and other distortions. In this paper, we present a model for the recognition of musical symbols through the use of a mobile application, whereby a camera is used to capture the input image; therefore, additional difficulties arise due to variations of the illumination and distortions. For our proposed model, we first generate a line adjacency graph (LAG) to remove the staff lines and to perform primitive detection. After symbol segmentation using the primitive information, we use a covariance-matching method to estimate the similarity between every symbol and pre-defined templates. This method generates the three hypotheses with the highest scores for likelihood measurement. We also add a global consistency (time measurements) to verify the three hypotheses in accordance with the structure of the musical sheets; one of the three hypotheses is chosen through a final decision. The results of the experiment show that our proposed method leads to promising results.

은닉 마르코프 모형을 이용한 회전체 결함신호의 패턴 인식 (Pattern Recognition of Rotor Fault Signal Using Bidden Markov Model)

  • 이종민;김승종;황요하;송창섭
    • 대한기계학회논문집A
    • /
    • 제27권11호
    • /
    • pp.1864-1872
    • /
    • 2003
  • Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.

입원 스트레스가 수면형태에 미치는 영향(Johnson의 간호모형 적용) (A Study on the Effects of the Hospitalization Stress on the Sleep Pattern)

  • 이소우
    • 대한간호학회지
    • /
    • 제16권2호
    • /
    • pp.36-43
    • /
    • 1986
  • The main purpose of this study was to explore the effect of the stress of hospitalization on the sleep pattern. Additionaly, this study was also to demonstrate how Johnson's nursing model may be applied to as nursing process. 104 hospitalized patients on surgical and medical wards were asked to rate 49 stress producing events associated with experience of hospitalization and sleep pattern scale. Five university hospitals were used as the setting for this study. Data for the study were collected by patient interview during hospitalization, self-reports and review of charts. For the analysis of the data, the pearson's correlation analysis of covariance and regression analysis were used. The results of this study were stated as follows; 1. The mean of the hospital stress scores was 111.261(S.D.=26.160). This means that the level of the hospitalization stress is high. The mean of the sleep pattern scores was 12.204(S.D. =2.615) This means that the characteristic's of the sleep pattern is poor. 2. The relationship between the hospitalization stress and sleep pattern was statistically significant at .01 level. 3. The effect of the hospitalization stress influenced strongly on the sleep pattern after sex, trait anxiety as covariates controlled. 4. The hospitalization stress revealed a 12% pre-diction as an influenced factor for the sleep pattern. Therefore, It can he said that the hospital stress did contribute significantly to the characteristics of the sleep pattern. Johnson's model can he also said that it is useful for the the assessment and diagnosis in nursing process.

  • PDF

Bootstrap confidence intervals for classification error rate in circular models when a block of observations is missing

  • Chung, Hie-Choon;Han, Chien-Pai
    • Journal of the Korean Data and Information Science Society
    • /
    • 제20권4호
    • /
    • pp.757-764
    • /
    • 2009
  • In discriminant analysis, we consider a special pattern which contains a block of missing observations. We assume that the two populations are equally likely and the costs of misclassification are equal. In this situation, we consider the bootstrap confidence intervals of the error rate in the circular models when the covariance matrices are equal and not equal.

  • PDF

암환자의 수면장애 설명모형 (An Explanatory Model for Sleep Disorders in People with Cancer)

  • 김희선;오의금
    • 대한간호학회지
    • /
    • 제41권4호
    • /
    • pp.460-470
    • /
    • 2011
  • Purpose: The aim of this study was to develop and test an explanatory model for sleep disorders in people with cancer. A hypothetical model was constructed on the basis of a review of previous studies, literature, and sleep models, and 10 latent variables were used to construct a hypothetical model. Methods: Data were collected from April 19 to June 25, 2010, using self-report questionnaires. The sample was 291 outpatients with cancer who visited the oncology cancer center at a university hospital. Collected data were analyzed using SPSS Win 15.0 program for descriptive statistics and correlation analysis and AMOS 7.0 program for covariance structural analysis. Results: It appeared that overall fit index was good as ${\chi}^2/df=1.162$, GFI=.969, AGFI=.944, SRMR=.052, NFI=.881, NNFI=.969, CFI=.980, RMSEA=.024, CN=337 in the modified model. The explanatory power of this model for sleep disorders in people with cancer was 62%. Further, sleep disorders were influenced directly by cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and past sleep pattern. Conclusion: Findings suggest that nurses should assess past sleep pattern and consider the development of a comprehensive nursing intervention program to minimize the cancer symptom experience, dysfunctional beliefs and attitudes about sleep, and thus, reduce sleep disorders in people with cancer.

Deletion diagnostics in fitting a given regression model to a new observation

  • Kim, Myung Geun
    • Communications for Statistical Applications and Methods
    • /
    • 제23권3호
    • /
    • pp.231-239
    • /
    • 2016
  • A graphical diagnostic method based on multiple case deletions in a regression context is introduced by using the sampling distribution of the difference between two least squares estimators with and without multiple cases. Principal components analysis plays a key role in deriving this diagnostic method. Multiple case deletions of test statistic are also considered when a new observation is fitted to a given regression model. The result is useful for detecting influential observations in econometric data analysis, for example in checking whether the consumption pattern at a later time is the same as the one found before or not, as well as for investigating the influence of cases in the usual regression model. An illustrative example is given.

혼합모형을 이용한 체지방 반복측정자료에 대한 통계적 분석 (A statistical analysis of the fat mass repeated measures data using mixed model)

  • 조진남;장은재
    • Journal of the Korean Data and Information Science Society
    • /
    • 제24권2호
    • /
    • pp.303-310
    • /
    • 2013
  • 체지방 감량에 대한 효과를 분석하고자 실험에 참가한 체지방율이 30% 이상인 42명의 여대생을 대상으로 일반폰을 사용하는 그룹과 스마트폰을 사용하는 그룹으로 나누어서 측정자료를 2주 간격으로 정리하여 8주간에 걸친 체지방 및 관련자료를 얻었다. 이 실험자료를 바탕으로 혼합모형을 이용하여 분석한 결과 AR(1)의 공분산행렬이 가장 적합한 모형으로 선택되었으며, 시점 간의 상관계수는 0.838로 상당히 밀접한 관련을 보여주었다. AR(1)의 공분산행렬을 설정하여 분석한 결과 처리간의 차이에서 스마트폰의 사용자가 일반폰의 사용자보다 0.654kg 정도의 체지방 감량 효과를 보여주었으며, 시간이 지날수록 체지방 감소효과가 있음을 알 수 있다. 그러나 처리와 시간과의 교호작용은 존재하지 않는다. 또한 실험실시 전의 체지방값과 총콜레스테롤은 유의하게 나타났으며, 섭취하는 칼로리는 약간 관련이 있으나, 허리엉덩이비율은 유의하지 않는 것으로 판명되었다.