• 제목/요약/키워드: Analysis of variance

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Bayesian Analysis of Multivariate Threshold Animal Models Using Gibbs Sampling

  • Lee, Seung-Chun;Lee, Deukhwan
    • Journal of the Korean Statistical Society
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    • 제31권2호
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    • pp.177-198
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    • 2002
  • The estimation of variance components or variance ratios in linear model is an important issue in plant or animal breeding fields, and various estimation methods have been devised to estimate variance components or variance ratios. However, many traits of economic importance in those fields are observed as dichotomous or polychotomous outcomes. The usual estimation methods might not be appropriate for these cases. Recently threshold linear model is considered as an important tool to analyze discrete traits specially in animal breeding field. In this note, we consider a hierarchical Bayesian method for the threshold animal model. Gibbs sampler for making full Bayesian inferences about random effects as well as fixed effects is described to analyze jointly discrete traits and continuous traits. Numerical example of the model with two discrete ordered categorical traits, calving ease of calves from born by heifer and calving ease of calf from born by cow, and one normally distributed trait, birth weight, is provided.

Determinants of Variance Risk Premium (경제지표를 활용한 분산프리미엄의 결정요인 추정과 수익률 예측)

  • Yoon, Sun-Joong
    • Economic Analysis
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    • 제25권1호
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    • pp.1-33
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    • 2019
  • This paper examines the economic factors that are related to the dynamics of the variance risk premium, and specially, which economic factors are related to the forecasting power of the variance premium regarding future index returns. Eleven general economic variables, eight interest rate variables, and eleven sentiment-associated variables are used to figure out the relevant economic variables that affect the variance risk premium. According to our empirical results, the won-dollar exchange rates, foreign reserves, the historical/implied volatility, and interest rate variables all have significant coefficients. The highest adjusted R-squared is more than 65 percent, indicating their significant explanatory power of the variance risk premium. Next, to verify the economic variables associated with the predictability of the variance risk premium, we conduct forecasting regressions to predict future stock returns and volatilities for one to six months. Our empirical analysis shows that only the won-dollar exchange rate, among the many variables associated with the dynamics of the variance risk premium, has a significant forecasting ability regarding future index returns. These results are consistent with results found in previous studies, including Londono (2012) and Bollerslev et al. (2014), which show that the variance risk premium is related to global risk factors.

Goodness-of-fit test for mean and variance functions

  • Jung, Sin-Ho;Lee, Kee-Won
    • Journal of the Korean Statistical Society
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    • 제26권2호
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    • pp.199-210
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    • 1997
  • Using regression methods based on quasi-likelihood equation, one only needs to specify the conditional mean and variance functions for the response variable in the analysis. In this paper, an omnibus lack-of-fit test is proposed to test the validity of these two functions. Our test is consistent against the alternative under which either the mean or the variance is not the one specified in the null hypothesis. The large-sample null distribution of our test statistics can be approximated through simulations. Extensive numerical studies are performed to demonstrate that the new test preserves the prescribed type I error probability. Power comparisons are conducted to show the advantage of the new proposal.

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A New Type of Clustering Problem with Two Objectives (복수 목적함수를 갖는 새로운 형태의 집단분할 문제)

  • Lee, Jae-Yeong
    • Journal of Korean Institute of Industrial Engineers
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    • 제24권1호
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    • pp.145-156
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    • 1998
  • In a classical clustering problem, grouping is done on the basis of similarities or distances (dissimilarities) among the elements. Therefore, the objective is to minimize the variance within each group while maximizing the between-group variance among all groups. In this paper, however, a new class of clustering problem is introduced. We call this a laydown grouping problem (LGP). In LGP, the objective is to minimize both the within-group and between-group variances. Furthermore, the problem is expanded to a multi-dimensional case where the two-way minimization process must be considered for each dimension simultaneously for all measurement characteristics. At first, the problem is assessed by analyzing its variance structures and their complexities by conjecturing that LGP is NP-complete. Then, the simulated annealing (SA) algorithm is applied and the results are compared against that from others.

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A Control Scheme for a Gradual Drift in the Process Variance

  • Kang, Hunku
    • Journal of Korean Society of Industrial and Systems Engineering
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    • 제23권56호
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    • pp.83-92
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    • 2000
  • This paper presents a study on control schemes for gradual increases (drifts) in a process variance. A new control chart, the Drifting Variance Control Chart (DVCC) is designed using Likelihood Ratio Test (LRT), and the ARL performance of the chart is evaluated for different subgroup sizes. The performance of this chart is then compared to some of the popular control schemes for the process dispersion, like the Shewhart S$^2$chart, the CUSUM chart and the EWMA chart. Results are presented and discussed. Also included is a sensitivity analysis that investigates how the DVCC performs when applied to a stepped change in process variance.

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Heuristic Process Capability Indices Using Distribution-decomposition Methods (분포분할법을 이용한 휴리스틱 공정능력지수의 비교 분석)

  • Chang, Youngsoon
    • Journal of Korean Society for Quality Management
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    • 제41권2호
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    • pp.233-248
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    • 2013
  • Purpose: This study develops heuristic process capability indices (PCIs) using distribution-decomposition methods and evaluates the performances. The heuristic methods decompose the variation of a quality characteristic into upper and lower deviations and adjust the value of the PCIs using decomposed deviations in accordance with the skewness. The weighted variance(WV), new WV(NWV), scaled WV(SWV), and weighted standard deviation(WSD) methods are considered. Methods: The performances of the heuristic PCIs are investigated under the varied situations such as various skewed distributions, sample sizes, and specifications. Results: WV PCI is the best under the normal populations, WSD and SWV PCIs are the best under the low skewed populations, NWV PCI is the best under the moderate and high skewed populations. Conclusion: Comprehensive analysis shows that the NWV method is most adequate for a practical use.

Mean-Variance Analysis for Optimal Operation and Supply Chain Coordination in a Green Supply Chain

  • Yamaguchi, Shin;Goto, Hirofumi;Kusukawa, Etsuko
    • Industrial Engineering and Management Systems
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    • 제16권1호
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    • pp.22-43
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    • 2017
  • It is urgently-needed to construct a green supply chain (GSC) from collection of used products through recycling of them to sales of products using the recycled parts. Besides, it is necessary to consider the uncertainty in product demand as a risk in a GSC. This study proposes the optimal operations for a GSC with a retailer and a manufacturer. A retailer pays an incentive for collection of used products from customers and sells a single type of products in a market. A manufacturer produces the products ordered by the retailer, using recyclable parts with acceptable quality and compensates the collection cost of used products as to the recycled parts. This paper discusses the following risk attitudes: risk-neutral attitude, risk-averse attitude, and risk-prone attitude. Using mean-variance analysis, the optimal decisions for product order quantity, collection incentive, and lower limit of quality level, in the decentralized GSC (DGSC) and the integrated GSC (IGSC) are made. DGSC optimizes the utility function of each member. IGSC does that of the whole system. The analysis numerically investigates how (i) risk attitude and (ii) quality of recyclable parts affect the optimal operations. Supply chain coordination between GSC members to shift IGSC from DGSC is discussed.

Characteristics and Classification of the Lower Body Somatotype of Junior High School Girls through Side View Silhouette (여중생의 하반신 측면체형의 분류 및 특성)

  • 임지영;김혜경
    • Journal of the Korean Society of Clothing and Textiles
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    • 제22권3호
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    • pp.333-340
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    • 1998
  • The purpose of this study was to classify the lower body somatotype based on the side view and to analyze the characteristics of each somatotype. The subject were 234 Korean Junior High School Girls. Data were collected through photographic sources and analyzed by factor analysis, cluster analysis and analysis of variance. The result of factor analysis indicated that 4 factors were extracted through factor analysis and those factorscomprised 73.5% of total variance. Using factor scores, cluster analysis was carried out and the subject were classified into 3 clusters. Each cluster was classified as their lower bobs side view contour.

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Comparison of Two Meta-Analysis Methods: Inverse-Variance-Weighted Average and Weighted Sum of Z-Scores

  • Lee, Cue Hyunkyu;Cook, Seungho;Lee, Ji Sung;Han, Buhm
    • Genomics & Informatics
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    • 제14권4호
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    • pp.173-180
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    • 2016
  • The meta-analysis has become a widely used tool for many applications in bioinformatics, including genome-wide association studies. A commonly used approach for meta-analysis is the fixed effects model approach, for which there are two popular methods: the inverse variance-weighted average method and weighted sum of z-scores method. Although previous studies have shown that the two methods perform similarly, their characteristics and their relationship have not been thoroughly investigated. In this paper, we investigate the optimal characteristics of the two methods and show the connection between the two methods. We demonstrate that the each method is optimized for a unique goal, which gives us insight into the optimal weights for the weighted sum of z-scores method. We examine the connection between the two methods both analytically and empirically and show that their resulting statistics become equivalent under certain assumptions. Finally, we apply both methods to the Wellcome Trust Case Control Consortium data and demonstrate that the two methods can give distinct results in certain study designs.

A Study on Taguchi and VTA Methods for Product Design (제품설계를 위한 다구찌 방법과 VTA방법에 관한 연구)

  • 장현수;김용범;김우열
    • Journal of the military operations research society of Korea
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    • 제27권1호
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    • pp.101-113
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    • 2001
  • Taguchi and VTA(variation Transmission Analysis) methods have been widely used recently as new methods for product design. In this study, Taguchi method using analysis of variance and VTA method using regression analysis are reviewed and compared with each other in terms of parameter design and tolerance design. In analysis of variance, variation of quality characteristics arises from noise factors, therefore the optimal levels of design factors are selected to minimize the effect of noise factors. n regression analysis, variation of quality characteristics arises from variation of each own design factors. As a method to reduce variation of these quality characteristics, sensitivity analysis was performed for each design factors. An example of calculating tolerance interval for the given defect rate in PPM is also introduced. Especially, the new method is suggested to increase the estimation accuracy of variation of quality characteristics through regression analysis.

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