• Title/Summary/Keyword: regression function

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Effect of Dimension Reduction on Prediction Performance of Multivariate Nonlinear Time Series

  • Jeong, Jun-Yong;Kim, Jun-Seong;Jun, Chi-Hyuck
    • Industrial Engineering and Management Systems
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    • v.14 no.3
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    • pp.312-317
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    • 2015
  • The dynamic system approach in time series has been used in many real problems. Based on Taken's embedding theorem, we can build the predictive function where input is the time delay coordinates vector which consists of the lagged values of the observed series and output is the future values of the observed series. Although the time delay coordinates vector from multivariate time series brings more information than the one from univariate time series, it can exhibit statistical redundancy which disturbs the performance of the prediction function. We apply dimension reduction techniques to solve this problem and analyze the effect of this approach for prediction. Our experiment uses delayed Lorenz series; least squares support vector regression approximates the predictive function. The result shows that linearly preserving projection improves the prediction performance.

Adaptive Robust Regression for Censored Data (중도 절단된 자료에 대한 적은 로버스트 회귀)

  • Kim, Chul-Ki
    • Journal of Korean Society for Quality Management
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    • v.27 no.2
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    • pp.112-125
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    • 1999
  • In a robust regression model, it is typically assumed that the errors are normally distributed. However, what if the error distribution is deviated from the normality and the response variables are not completely observable due to censoring? For complete data, Kim and Lai(1998) suggested a new adaptive M-estimator with an asymptotically efficient score function. The adaptive M-estimator is based on using B-splines to estimate the score function and simple cross validation to determine the knots of the B-splines, which are a modified version of Kun( 1992). We herein extend this method to right-censored data and study how well the adaptive M-estimator performs for various error distributions and censoring rates. Some impressive simulation results are shown.

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Influencing Factors of Mentoring on Nursing Students (멘토링의 영향요인: 간호대학생을 대상으로)

  • Seol-Young Bang
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.5
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    • pp.733-741
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    • 2023
  • The purpose his study was a descriptive research study to identify the influencing factors of mentoring for nursing students, and was conducted with 120 nursing students. The collected data were subjected to real number and percentage, mean and standard deviation, t-test, ANOVA, Scheffe test, Pearson's correlation, and multiple regression analysis using SPSS/WIN 25.0. As a result of the study, mentoring was found to have a significant positive correlation with organizational socialization, core nursing competency, and clinical performance competency, and the explanatory power of the regression model was 64.1%. Since mentoring is an effective teaching method, based on this study, we propose a study to develop a structured mentoring program including organizational socialization, core nursing competency, and clinical performance competency to test the effectiveness. In addition, proposes a study to identify the relationship with various variables by dividing mentoring into sub-competencies of career development function, psychological stability function, and role model function.

Development of Fuzzy Membership Function for Emotional Satisfaction Quantification (감성 만족도의 정량화를 위한 퍼지 소속 함수 개발)

  • Park, Jun-Seok;Myeong, No-Hae
    • Journal of the Ergonomics Society of Korea
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    • v.23 no.2
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    • pp.37-54
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    • 2004
  • Fuzzy theory provides an intelligence treatment model for judgement about information when it needs a solution or a decision making about vague problems. Therefore, fuzzy theory is used for appropriate evaluation and decision on obscure information as human's emotion in human factors, In previous study, fuzzy membership function is defined for judgement infOlmation as human's emotion then ultimate results are deducted through fuzzy inference model. This method uses general CWTent through literature review or max, min and average as representative statics value about considering variables. But, this method makes away with nonlinear's or inegular's factors of human sensibility. Accordingly, application of this method leads to considerable loss of information in the ultimate evaluation. For that reason, this method has a limitation in objective evaluation of human factors. So, this study focuses on development of fuzzy membership function, which evaluates human's emotion or feeling accurately and objectively. We used the regression analysis and reasoned a fuzzy membership function about the relation of the variables. Then we verified the adequacy with the reliability through the experiment after this.

A FFP-based Model to Estimate Software Development Cost (소프트웨어 개발비용을 추정하기 위한 FFP 기반 모델)

  • Park, Ju-Seok;Chong, Ki-Won
    • The KIPS Transactions:PartD
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    • v.10D no.7
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    • pp.1137-1144
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    • 2003
  • The existing Function Point method to estimate the software size has been utilized frequently with the management information system. Due to the expanding usage of the real-time and embedded system, the Full Function Point method is being proposed. However, despite many research is being carried out relation to the software size, the research on the model to estimate the development cost from the measured software size is inadequate. This paper analyzed the linear regression model and power regression model which estimate the development cost from the software FFP The power model is selected, which shows its estimation is most adequate.

Influence of Cognitive Function and Depressive Symptoms on Instrumental Activities of Daily Living in Community-dwelling Older Adults (지역사회 노인의 인지기능과 우울감이 도구적 일상생활동작에 미치는 영향)

  • Seo, Kawoun;Song, Youngshin
    • The Korean Journal of Rehabilitation Nursing
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    • v.19 no.2
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    • pp.71-81
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    • 2016
  • Purpose: The purpose of this study was to explore the influence of cognitive function and depressive symptoms on instrumental activities of daily living (IADL) in addition to identify the factors associated with IADL in community-dwelling older adults. Methods: This was a descriptive study with cross-sectional design. Data were collected from July 2013 to June 2014. A total of 143 participants without dementia, depression and disability were enrolled in this study. Cognitive function was measured using Seoul verbal learning test (SVLT), digital span (forward/backward) and fist-edge-palm test. The Korean-IADL and Short Geriatric Depression Scale (S-GDS) were used. Data analysis was performed using descriptive statistics, t-test, ANOVA, Pearson's correlation coefficient, and hierarchical regression. Results: Overall, a multiple regression model revealed that approximately 27.4% of total variability in IADL in the sample of community-dwelling older adults could be explained by the significant 12 variables in this model ($R^2=0.274$, F=5.467, p<.001). Age, having religion and cognitive function were the predictors of IADL in community-dwelling older adults. Conclusion: This study suggest that we need to monitor cognitive function in older to maintain the ability for IADL in older adults. Also, individualized program for improving older adults' IADL should be included in nursing intervention.

A Study on the Local Regression Rate of Solid Fuel in Hybrid Rocket (하이브리드 로켓에서의 고체연료의 국부 후퇴율에 관한 연구)

  • Kim, Soojong;Lee, Jungpyo;Kim, Gihun;Cho, Jungtae;Kim, Hakchul;Woo, Kyoungjin;Moon, Heejang;Sung, Hong-Gye;Kim, Jin-Kon
    • Journal of Aerospace System Engineering
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    • v.2 no.4
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    • pp.1-6
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    • 2008
  • In generally, the regression rate was expressed with average value and oxidizer mass flux in hybrid propulsion system. This can not represent the local value of regression rate along with oxidizer flow direction. In this study, experimental studies were performed with Separation method and Cutting method for measure local regression rate. In axial injection, the local regression rate decreases rapidly with axial location near entrance and increases with axial direction from the leading edge and the empirical formula for local regression rate with function of oxidizer mass flux and location was derived. Swirl injection regression rate has higher value at the leading edge of the fuel and comparatively uniform regression rate at the downstream. Overall regression rate of swirl injection is higher increased about 54 % than regression rate of axial injection.

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Nonparametric Kernel Regression Function Estimation with Bootstrap Method

  • Kim, Dae-Hak
    • Journal of the Korean Statistical Society
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    • v.22 no.2
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    • pp.361-368
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    • 1993
  • In recent years, kernel type estimates are abundant. In this paper, we propose a bandwidth selection method for kernel regression of fixed design based on bootstrap procedure. Mathematical properties of proposed bootstrap-based bandwidth selection method are discussed. Performance of the proposed method for small sample case is compared with that of cross-validation method via a simulation study.

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Fuzzy c-Logistic Regression Model in the Presence of Noise Cluster

  • Alanzado, Arnold C.;Miyamoto, Sadaaki
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.431-434
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    • 2003
  • In this paper we introduce a modified objective function for fuzzy c-means clustering with logistic regression model in the presence of noise cluster. The logistic regression model is commonly used to describe the effect of one or several explanatory variables on a binary response variable. In real application there is very often no sharp boundary between clusters so that fuzzy clustering is often better suited for the data.

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Local Bandwidth Selection for Nonparametric Regression

  • Lee, Seong-Woo;Cha, Kyung-Joon
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.453-463
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    • 1997
  • Nonparametric kernel regression has recently gained widespread acceptance as an attractive method for the nonparametric estimation of the mean function from noisy regression data. Also, the practical implementation of kernel method is enhanced by the availability of reliable rule for automatic selection of the bandwidth. In this article, we propose a method for automatic selection of the bandwidth that minimizes the asymptotic mean square error. Then, the estimated bandwidth by the proposed method is compared with the theoretical optimal bandwidth and a bandwidth by plug-in method. Simulation study is performed and shows satisfactory behavior of the proposed method.

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