• Title/Summary/Keyword: Beta distribution model

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An Attempt to Model Distributions of Machined Component Dimensions in Production

  • Cogun, Can;Kilinc, Biinyamin
    • Journal of Mechanical Science and Technology
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    • v.16 no.1
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    • pp.60-74
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    • 2002
  • In this study, normal, log-normal, triangular, uniform. Weibull, Erlang and unit beta probability density functions are tried to represent the behaviour of frequency distributions of workpiece dimensions collected from various manufacturing firms. Among the distribution functions, the unit beta distribution function is found to be the best fit using the chi-square test of fit. An attempt is made for the adoption of the unit beta model to x-bar charts of quality control in manufacturing. In this direction, upper and lower control limits (UCL and LCL) of x-bar control charts of dimension measurements are estimated for the beta model, and the observed differences between the beta and normal model control limits are discussed for the measurement sets.

Summary on Internet Communication Network Quality Characteristics Using Beta Probability Distribution (베타 확률분포를 이용한 인터넷통신 네트워크 품질특성 요약)

  • Park Sung-Min
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1661-1662
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    • 2006
  • Internet communication network quality characteristics are analyzed using Beta probability distribution. Beta probability distribution is chosen for the underlying probability distribution because it is an extremely flexible probability distribution used to model bounded random variables. Based on the fitted Beta probability distribution, a dataset regarding each network quality characteristic is summarized concisely.

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An Hourly Extreme Data Estimation Method Developed Using Nonstationary Bayesian Beta Distribution (비정상성 Bayesian Beta 분포를 이용한 시 단위 극치자료 추정기법 개발)

  • Kim, Yong-Tak;Kim, Jin-Young;Lee, Jae Chul;Kwon, Hyun-Han
    • Journal of Korean Society on Water Environment
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    • v.33 no.3
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    • pp.256-272
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    • 2017
  • Extreme rainfall has become more frequent over the Korean peninsula in recent years, causing serious damages. In a changing climate, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to overestimate (or underestimate) the design rainfalls. A main objective of this study is to develop a stochastic disaggregation method of seasonal rainfall to hourly extreme rainfall, and offer a way to derive the nonstationary IDF curves. In this study, we propose a novel approach based on a Four-Parameter Beta (4P-beta) distribution to estimate the nonstationary IDF curves conditioned on the observed (or simulated) seasonal rainfall, which becomes the time-varying upper bound of the 4P beta distribution. Moreover, this study employed a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters. The proposed model showed a comparable design rainfall to that of GEV distribution under the stationary assumption. As a nonstationary rainfall frequency model, the proposed model can effectively translate the seasonal variation into the sub-daily extreme rainfall.

Predicting Harvest Maturity of the 'Fuji' Apple using a Beta Distribution Phenology Model based on Temperature (온도기반의 Beta Distribution Model 을 이용한 후지 사과의 성숙기 예측)

  • Choi, In-Tae;Shim, Kyo-Moon;Kim, Yong-Seok;Jung, Myung-Pyo
    • Journal of Environmental Science International
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    • v.26 no.11
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    • pp.1247-1253
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    • 2017
  • The Fuji variety of apple, introduced in Japan, has excellent storage quality and good taste, such that it is the most commonly cultivated apple variety in Gunwi County, North Gyeongsang Province, Korean Peninsula. Accurate prediction of harvest maturity allows farmers to more efficiently manage their farm in important aspects such as working time, fruit storage, market shipment, and labor distribution. Temperature is one of the most important factors that determine plant growth, development, and yield. This paper reports on the beta distribution (function) model that can be used to simulate the the phenological response of plants to temperature. The beta function, commonly used as a skewed probability density in statistics, was introduced to estimate apple harvest maturity as a function of temperature in this study. The model parameters were daily maximum temperature, daily optimum temperature, and maximum growth rate. They were estimated from the input data of daily maximum and minimum temperature and apple harvest maturity. The difference in observed and predicted maturity day from 2009 to 2012, with optimal parameters, was from two days earlier to one day later.

Asymptotic Expansion of the Distribution of a Studentized Test Statistic for the Slope Parameter in a Simple Linear Structural Relationship

  • Chang, Kyung;Dahm, P. Frederic
    • Journal of Korean Society for Quality Management
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    • v.21 no.1
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    • pp.171-180
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    • 1993
  • Variables, x and y are said to have a linear relation if $y={\beta}_0+{\beta}_1\;x$, and ${\beta}_0$ and ${\beta}_1$ are constants. The relationship is called a structural relationship if x has positive variance (i.e., x is not fixed) and only error-prone measurements of x and y can be obtained. This paper derives (to order $n^{+1/2}$) an approximate distribution of the Studentized test statistic for testing hypotheses about the slope parameter, ${\beta}_1$ in a simple linear structural model. A simulation study suggests our approximate distribution is more accurate approximation to the exact distributions of the Studentized statistic than is the limiting distribution.

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Bayesian Inferences for Software Reliability Models Based on Beta-Mixture Mean Value Functions

  • Nam, Seung-Min;Kim, Ki-Woong;Cho, Sin-Sup;Yeo, In-Kwon
    • The Korean Journal of Applied Statistics
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    • v.21 no.5
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    • pp.835-843
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    • 2008
  • In this paper, we investigate a Bayesian inference for software reliability models based on mean value functions which take the form of the mixture of beta distribution functions. The posterior simulation via the Markov chain Monte Carlo approach is used to produce estimates of posterior properties. Its applicability is illustrated with two real data sets. We compute the predictive distribution and the marginal likelihood of various models to compare the performance of them. The model comparison results show that the model based on the beta-mixture performs better than other models.

An Application of the Smart Beta Portfolio Model: An Empirical Study in Indonesia Stock Exchange

  • WASPADA, Ika Putera;SALIM, Dwi Fitrizal;FARISKA, Putri
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.9
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    • pp.45-52
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    • 2021
  • Stock price fluctuations affect investor returns, particularly, in this pandemic situation that has triggered stock market shocks. As a result of this situation, investors prefer to move their money into a safer portfolio. Therefore, in this study, we approach an efficient portfolio model using smart beta and combining others to obtain a fast method to predict investment stock returns. Smart beta is a method to selects stocks that will enter a portfolio quickly and concisely by considering the level of return and risk that has been set according to the ability of investors. A smart beta portfolio is efficient because it tracks with an underlying index and is optimized using the same techniques that active portfolio managers utilize. Using the logistic regression method and the data of 100 low volatility stocks listed on the Indonesia stock exchange from 2009-2019, an efficient portfolio model was made. It can be concluded that an efficient portfolio is formed by a group of stocks that are aggressive and actively traded to produce optimal returns at a certain level of risk in the long-term period. And also, the portfolio selection model generated using the smart beta, beta, alpha, and stock variants is a simple and fast model in predicting the rate of return with an adjusted risk level so that investors can anticipate risks and minimize errors in stock selection.

POSTERIOR COMPUTATION OF SURVIVAL MODEL WITH DISCRETE APPROXIMATION

  • Lee, Jae-Yong;Kwon, Yong-Chan
    • Journal of the Korean Statistical Society
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    • v.36 no.2
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    • pp.321-333
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    • 2007
  • In the proportional hazard model with the beta process prior, the posterior computation with the discrete approximation is considered. The time period of interest is partitioned by small intervals. On each partitioning interval, the likelihood is approximated by that of a binomial experiment and the beta process prior is by a beta distribution. Consequently, the posterior is approximated by that of many independent binomial model with beta priors. The analysis of the leukemia remission data is given as an example. It is illustrated that the length of the partitioning interval affects the posterior and one needs to be careful in choosing it.

Development of a p Control Chart for Overdispersed Process with Beta-Binomial Model (베타-이항모형을 이용한 과산포 공정용 p 관리도의 개발)

  • Bae, Bong-Soo;Seo, Sun-Keun
    • Journal of Korean Society for Quality Management
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    • v.45 no.2
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    • pp.209-225
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    • 2017
  • Purpose: Since traditional p chart is unable to deal with the variation of attribute data, this paper proposes a new attribute control chart for nonconforming proportions incorporating overdispersion with a beta-binomial model. Methods: Statistical theories for control chart developed under the beta-binomial model and a new approach using this control chart are presented Results: False alarm probabilities of p chart with the beta-binomial model are evaluated and demerits of p chart under overdispersion are discussed from three examples. Hence a concrete procedure for the proposed control chart is provided and illustrated with examples Conclusion: The proposed chart is more useful than traditional p chart, individual chart to treat observed proportions nonconforming as variable data and Laney p' chart.

Spatializing beta-diversity of vascular plants - Application of Generalized Dissimilarity Model in the Republic of Korea - (식생 베타 다양성의 공간화 기법 연구 - Generalized Dissimilarity Model의 국내적용 및 활용 -)

  • Choi, Yu-Young
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.25 no.3
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    • pp.29-45
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    • 2022
  • For biodiversity conservation, the importance of beta-diversity which is changes in the composition of species according to environmental changes has become emphasized. However, given the systematic investigation of species distribution and the accumulation of large amounts of data in the Republic of Korea(ROK), research on the spatialization of beta-diversity using them is insufficient. Accordingly, this research investigated the applicability of the Generalized Dissimilarity Modeling(GDM) to ROK, which can predict and map the similarity of compositional turnover (beta-diversity) based on environmental variables. A brief overview of the statistical description on using GDM was presented, and a model was fitted using the flora distribution data(410,621points) from the National Ecosystem Survey and various environmental spatial data including climate, soil, topography, and land cover. Procedures and appropriated spatial units required to improve the explanatory power of the model were presented. As a result, it was found that geographical distance, temperature annual range, summer temperature, winter precipitation, and soil factors affect the dissimilarity of the vegetation community composition. In addition, as a result of predicting the similarity of vegetation composition across the nation, and classifying them into 20 and 100 zones, the similarity was high mainly in the central inland area, and tends to decrease toward the mountainous areas, southern coastal regions, and island including Jeju island, which means the composition of the vegetation community is unique and beta diversity is high. In addition, it was identified that the number of common species between zones decreased as the geographic distance between zones increased. It classified the spatial distribution of plant community composition in a quantitative and objective way, but additional research and verification are needed for practical application. It is expected that research on community-level biodiversity modeling in the ROK will be conducted more actively based on this study.