• Title/Summary/Keyword: reduced-rank regression

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Variable Selection with Nonconcave Penalty Function on Reduced-Rank Regression

  • Jung, Sang Yong;Park, Chongsun
    • Communications for Statistical Applications and Methods
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    • v.22 no.1
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    • pp.41-54
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    • 2015
  • In this article, we propose nonconcave penalties on a reduced-rank regression model to select variables and estimate coefficients simultaneously. We apply HARD (hard thresholding) and SCAD (smoothly clipped absolute deviation) symmetric penalty functions with singularities at the origin, and bounded by a constant to reduce bias. In our simulation study and real data analysis, the new method is compared with an existing variable selection method using $L_1$ penalty that exhibits competitive performance in prediction and variable selection. Instead of using only one type of penalty function, we use two or three penalty functions simultaneously and take advantages of various types of penalty functions together to select relevant predictors and estimation to improve the overall performance of model fitting.

Joint Test for Seasonal Cointegrating Ranks

  • Seong, Byeong-Chan;Yi, Yoon-Ju
    • Communications for Statistical Applications and Methods
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    • v.15 no.5
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    • pp.719-726
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    • 2008
  • In this paper we consider a joint test for seasonal cointegrating(CI) ranks that enables us to simultaneously model cointegrated structures across seasonal unit roots in seasonal cointegration. A CI rank test for a single seasonal unit root is constructed and extended to a joint test for multiple seasonal unit roots. Their asymptotic distributions and selected critical values for the joint test are obtained. Through a small Monte Carlo simulation study, we evaluate performances of the tests.

Common Feature Analysis of Economic Time Series: An Overview and Recent Developments

  • Centoni, Marco;Cubadda, Gianluca
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.415-434
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    • 2015
  • In this paper we overview the literature on common features analysis of economic time series. Starting from the seminal contributions by Engle and Kozicki (1993) and Vahid and Engle (1993), we present and discuss the various notions that have been proposed to detect and model common cyclical features in macroeconometrics. In particular, we analyze in details the link between common cyclical features and the reduced-rank regression model. We also illustrate similarities and differences between the common features methodology and other popular types of multivariate time series modelling. Finally, we discuss some recent developments in this area, such as the implications of common features for univariate time series models and the analysis of common autocorrelation in medium-large dimensional systems.

Predicting Korea Pro-Baseball Rankings by Principal Component Regression Analysis (주성분회귀분석을 이용한 한국프로야구 순위)

  • Bae, Jae-Young;Lee, Jin-Mok;Lee, Jea-Young
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.367-379
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    • 2012
  • In baseball rankings, prediction has been a subject of interest for baseball fans. To predict these rankings, (based on 2011 data from Korea Professional Baseball records) the arithmetic mean method, the weighted average method, principal component analysis, and principal component regression analysis is presented. By standardizing the arithmetic average, the correlation coefficient using the weighted average method, using principal components analysis to predict rankings, the final model was selected as a principal component regression model. By practicing regression analysis with a reduced variable by principal component analysis, we propose a rank predictability model of a pitcher part, a batter part and a pitcher batter part. We can estimate a 2011 rank of pro-baseball by a predicted regression model. By principal component regression analysis, the pitcher part, the other part, the pitcher and the batter part of the ranking prediction model is proposed. The regression model predicts the rankings for 2012.

Analyzing empirical performance of correlation based feature selection with company credit rank score dataset - Emphasis on KOSPI manufacturing companies -

  • Nam, Youn Chang;Lee, Kun Chang
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.4
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    • pp.63-71
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    • 2016
  • This paper is about applying efficient data mining method which improves the score calculation and proper building performance of credit ranking score system. The main idea of this data mining technique is accomplishing such objectives by applying Correlation based Feature Selection which could also be used to verify the properness of existing rank scores quickly. This study selected 2047 manufacturing companies on KOSPI market during the period of 2009 to 2013, which have their own credit rank scores given by NICE information service agency. Regarding the relevant financial variables, total 80 variables were collected from KIS-Value and DART (Data Analysis, Retrieval and Transfer System). If correlation based feature selection could select more important variables, then required information and cost would be reduced significantly. Through analysis, this study show that the proposed correlation based feature selection method improves selection and classification process of credit rank system so that the accuracy and credibility would be increased while the cost for building system would be decreased.

Dietary patterns based on carbohydrate nutrition are associated with the risk for diabetes and dyslipidemia

  • Song, Su-Jin;Lee, Jung-Eun;Paik, Hee-Young;Park, Min-Sun;Song, Yoon-Ju
    • Nutrition Research and Practice
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    • v.6 no.4
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    • pp.349-356
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    • 2012
  • Several studies have been conducted on dietary patterns based on carbohydrate nutrition in Asian populations. We examined the cross-sectional associations in dietary patterns based on carbohydrate nutrition, including the glycemic index (GI) with dyslipidemia and diabetes among the Korean adult population. We analyzed 9,725 subjects (3,795 men and 5,930 women, ${\geq}$ 20 years) from the Fourth Korea National Health and Nutrition Examination Survey. Dietary information was collected using single 24-hour recall. Reduced rank regression was used to derive dietary patterns from 22 food groups as predictor variables and four dietary factors related to the quantity and quality of carbohydrates as response variables. Two dietary patterns were identified: 1) the balanced pattern was characterized by high intake of various kinds of foods including white rice, and 2) the rice-oriented pattern was characterized by a high intake of white rice but low intake of vegetables, fruits, meat, and dairy products. Both patterns had considerable amounts of total carbohydrate, but GI values differed. The rice-oriented pattern was positively associated with hypertriglyceridemia in men and low high density lipoprotein-cholesterol in both men and women. The balanced pattern had no overall significant association with the prevalence of dyslipidemia or diabetes, however, men with energy intake above the median showed a reduced prevalence of diabetes across quintiles of balanced pattern scores. The results show that dietary patterns based on carbohydrate nutrition are associated with prevalence of dyslipidemia and diabetes in the Korean adult population.

Dietary patterns are associated with physical growth among school girls aged 9-11 years

  • Noh, Hwa-Young;Song, Yoon-Ju;Lee, Jung-Eun;Joung, Hyo-Jee;Park, Min-Kyung;Li, Shan Ji;Paik, Hee-Young
    • Nutrition Research and Practice
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    • v.5 no.6
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    • pp.569-577
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    • 2011
  • The purpose of this study was to identify dietary patterns among Korean elementary school girls based on the change in body mass index (BMI), body fat, bone mineral density (BMD), and bone mineral content (BMC) during 22 months and to explore the characteristics of dietary patterns identified. Girls aged 9-11 years were recruited and 3-day dietary data were collected four times. Subjects with a diet record of 8 or more days and anthropometric data measured at baseline and 22 months later were included (n = 198). Reduced rank regression was utilized to derive dietary patterns using a change in BMI, body fat, and calcaneus BMD and BMC as response variables. Two dietary patterns were identified: the "Egg and Rice" dietary pattern and "Fruit, Nuts, Milk Beverage, Egg, Grain" (FNMBEG) dietary pattern. Subjects who had high score on the FNMBEG pattern consumed various food groups, including fruits, nuts and seeds, and dairy products, whereas subjects in the "Egg and Rice' dietary pattern group did not. Both dietary patterns showed a positive association with change in BMI and body fat. However, subjects who had a higher score on the "Egg and Rice" dietary pattern had less of a BMC increase, whereas subjects who had a higher score on the FMBEG dietary pattern had more increased BMC over 22 months after adjusting for age, body and bone mass, and Tanner stage at baseline. Our results provide evidence that a well-balanced diet contributes to lean body mass growth among young girls.

The Factors Influencing Empowerment of 119 Emergency Medical Technicians (119 구급대원의 임파워먼트에 영향을 미치는 요인)

  • Choo, Sung-Joo;Park, Ok-Im;Kang, Hee-Sun
    • Korean Journal of Occupational Health Nursing
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    • v.20 no.2
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    • pp.153-162
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    • 2011
  • Purpose: The purpose of this study is to investigate the impact of job stress, self-efficacy and empowerment of 119 Emergency medical technicians in Jeollanam-do. Methods: This study used the data collected from 346 respondents working for first aid in a fire station. To answer research questions, this study employed frequency analysis, reliability test, F (t)-test, ANOVA, Scheffe' post-hoc test, and multiple-regression analysis. Results: In terms of demographic characteristics, marital status and age had significant impact on job stress, but sex and education did not. In terms of job characteristics, first placement, rank, and tenure made significant difference on job stress, whereas certificate, department, and area did not. These results address that general characteristics, self-efficacy and job stress are critical variables on empowerment. Conclusion: From the research findings, it is concluded that fire fighters' job stress can be reduced if professional development programs are given to them, which is likely to provide better public services such as first aids and welfare, as well as to increase job satisfaction.

Glycemic Index and Glycemic Load Dietary Patterns and the Associated Risk of Breast Cancer: A Case-control Study

  • Woo, Hae Dong;Park, Ki-Soon;Shin, Aesun;Ro, Jungsil;Kim, Jeongseon
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.9
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    • pp.5193-5198
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    • 2013
  • The glycemic index (GI) and glycemic load (GL) have been considered risk factors for breast cancer, but association studies of breast cancer risk using simple GI and GL might be affected by confounding effects of the overall diet. A total of 357 cases and 357 age-matched controls were enrolled, and dietary intake was assessed using a validated food frequency questionnaire (FFQ) with 103 food items. GI and GL dietary patterns were derived by reduced rank regression (RRR) method. The GI and GL pattern scores were positively associated with breast cancer risk among postmenopausal women [OR (95%CI): 3.31 (1.06-10.39), p for trend=0.031; 9.24 (2.93-29.14), p for trend<0.001, respectively], while the GI pattern showed no statistically significant effects on breast cancer risk, and the GL pattern was only marginally significant, among premenopausal women (p for trend=0.043). The GI and GL pattern scores were positively associated with the risk of breast cancer in subgroups defined by hormone receptor status in postmenopausal women. The GI and GL patterns based on all food items consumed were positively associated with breast cancer.

Using ranked auxiliary covariate as a more efficient sampling design for ANCOVA model: analysis of a psychological intervention to buttress resilience

  • Jabrah, Rajai;Samawi, Hani M.;Vogel, Robert;Rochani, Haresh D.;Linder, Daniel F.;Klibert, Jeff
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.241-254
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    • 2017
  • Drawing a sample can be costly or time consuming in some studies. However, it may be possible to rank the sampling units according to some baseline auxiliary covariates, which are easily obtainable, and/or cost efficient. Ranked set sampling (RSS) is a method to achieve this goal. In this paper, we propose a modified approach of the RSS method to allocate units into an experimental study that compares L groups. Computer simulation estimates the empirical nominal values and the empirical power values for the test procedure of comparing L different groups using modified RSS based on the regression approach in analysis of covariance (ANCOVA) models. A comparison to simple random sampling (SRS) is made to demonstrate efficiency. The results indicate that the required sample sizes for a given precision are smaller under RSS than under SRS. The modified RSS protocol was applied to an experimental study. The experimental study was designed to obtain a better understanding of the pathways by which positive experiences (i.e., goal completion) contribute to higher levels of happiness, well-being, and life satisfaction. The use of the RSS method resulted in a cost reduction associated with smaller sample size without losing the precision of the analysis.