• Title/Summary/Keyword: ordered data

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Families of Distributions Arising from Distributions of Ordered Data

  • Ahmadi, Mosayeb;Razmkhah, M.;Mohtashami Borzadaran, G.R.
    • Communications for Statistical Applications and Methods
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    • v.22 no.2
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    • pp.105-120
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    • 2015
  • A large family of distributions arising from distributions of ordered data is proposed which contains other models studied in the literature. This extension subsume many cases of weighted random variables such as order statistics, records, k-records and many others in variety. Such a distribution can be used for modeling data which are not identical in distribution. Some properties of the theoretical model such as moment, mean deviation, entropy criteria, symmetry and unimodality are derived. The proposed model also studies the problem of parameter estimation and derives maximum likelihood estimators in a weighted gamma distribution. Finally, it will be shown that the proposed model is the best among the previously introduced distributions for modeling a real data set.

Processing-Node Status-based Message Scattering and Gathering for Multi-processor Systems on Chip

  • Park, Jongsu
    • Journal of information and communication convergence engineering
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    • v.17 no.4
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    • pp.279-284
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    • 2019
  • This paper presents processing-node status-based message scattering and gathering algorithms for multi-processor systems on chip to reduce the communication time between processors. In the message-scattering part of the message-passing interface (MPI) scatter function, data transmissions are ordered according to the proposed linear algorithm, based on the processor status. The MPI hardware unit in the root processing node checks whether each processing node's status is 'free' or 'busy' when an MPI scatter message is received. Then, it first transfers the data to a 'free' processing node, thereby reducing the scattering completion time. In the message-gathering part of the MPI gather function, the data transmissions are ordered according to the proposed linear algorithm, and the gathering is performed. The root node receives data from the processing node that wants to transfer first, and reduces the completion time during the gathering. The experimental results show that the performance of the proposed algorithm increases at a greater rate as the number of processing nodes increases.

Rank Test for Ordered Alternatives under Random Censorship

  • Gyu-Jin Jeong;Sang-Gue Park
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.195-204
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    • 1996
  • Some rank tests for comparing r treatments against ordered alternatives are proposed when some of data are randomly cemsored, which are the weighted logrank tests based on pairwise-ranking scheme. The covariances of the proposed test statistics are explicitly obtained from the results of the counting process theory and the test procedures are illustrated by a numerical example. Simulation studies are also performed for comparing with the other well-known tests.

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Tests For and Against a Positive Dependence Restriction in Two-Way Ordered Contingency Tables

  • Oh, Myongsik
    • Journal of the Korean Statistical Society
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    • v.27 no.2
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    • pp.205-220
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    • 1998
  • Dependence concepts for ordered two-way contingency tables have been of considerable interest. We consider a dependence concept which is less restrictive than likelihood ratio dependence and more restrictive than regression dependence. Maximum likelihood estimation of cell probability under this dependence restriction is studied. The likelihood ratio statistics for and against this dependence are proposed and their large sample distributions are derived. A real data is analyzed to illustrate the estimation and testing procedures.

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A Study on the Satisfaction of School meals about Elementary, Middle and High School's Students in Jeonbuk Area : An Ordered Probit Analysis (순위프로빗모형을 이용한 전북지역 초.중.고교 학생들의 학교급식에 대한 만족도 분석)

  • Lim, Sung-Soo;Yang, Jae-Seong
    • Korean Journal of Organic Agriculture
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    • v.21 no.4
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    • pp.539-554
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    • 2013
  • This study analyses the factors that affect the satisfaction of school meals program. To obtain the data, 54 elementary, middle and high schools in Jeonbuk area were chosen for survey. A ordered probit model analysis is conducted to identify the key explanatory variables that affect the satisfaction of school meals about elementary, middle and high school's students. Also, a ordered probit model is used to calculate marginal effects of several key variables. The study finds that key factors that affect to increase the satisfaction of school meals are rural area schools, elementary school's students, and education for school meals or food nutrition. The satisfaction of school meals in urban and rural school's students are significantly different. Also, the satisfaction of school meals about elementary, middle and high school's students are significantly different. To do this, importance of school meals is to build up the safe agricultural supply system. For safe agricultural supply system, local agricultural products provided in school meals should be supplied based on GAP, HACCP certificated companies such as US FTS(Farm to School) program.

Imputation for Binary or Ordered Categorical Traits Based on the Bayesian Threshold Model (베이지안 분계점 모형에 의한 순서 범주형 변수의 대체)

  • Lee Seung-Chun
    • The Korean Journal of Applied Statistics
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    • v.18 no.3
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    • pp.597-606
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    • 2005
  • The nonresponse in sample survey causes a problem when it comes time to analyze dataset in public-use files where the user has only complete-data methods available and has limited information about the reasons for nonresponse. Recently imputation for nonresponse is becoming a standard approach for handling nonresponse and various imputation methods have been devised . However, most imputation methods concern with continuous traits while many interesting features are measured by binary or ordered categorical scales in sample survey. In this note. an imputation method for ignorable nonresponse in binary or ordered categorical traits is considered.

Bayesian Estimation of k-Population Weibull Distribution Under Ordered Scale Parameters (순서를 갖는 척도모수들의 사전정보 하에 k-모집단 와이블분포의 베이지안 모수추정)

  • 손영숙;김성욱
    • The Korean Journal of Applied Statistics
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    • v.16 no.2
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    • pp.273-282
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    • 2003
  • The problem of estimating the parameters of k-population Weibull distributions is discussed under the prior of ordered scale parameters. Parameters are estimated by the Gibbs sampling method. Since the conditional posterior distribution of the shape parameter in the Gibbs sampler is not log-concave, the shape parameter is generated by the adaptive rejection sampling. Finally, we applied this estimation methodology to the data discussed in Nelson (1970).

Bayesian inference for an ordered multiple linear regression with skew normal errors

  • Jeong, Jeongmun;Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • v.27 no.2
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    • pp.189-199
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    • 2020
  • This paper studies a Bayesian ordered multiple linear regression model with skew normal error. It is reasonable that the kind of inherent information available in an applied regression requires some constraints on the coefficients to be estimated. In addition, the assumption of normality of the errors is sometimes not appropriate in the real data. Therefore, to explain such situations more flexibly, we use the skew-normal distribution given by Sahu et al. (The Canadian Journal of Statistics, 31, 129-150, 2003) for error-terms including normal distribution. For Bayesian methodology, the Markov chain Monte Carlo method is employed to resolve complicated integration problems. Also, under the improper priors, the propriety of the associated posterior density is shown. Our Bayesian proposed model is applied to NZAPB's apple data. For model comparison between the skew normal error model and the normal error model, we use the Bayes factor and deviance information criterion given by Spiegelhalter et al. (Journal of the Royal Statistical Society Series B (Statistical Methodology), 64, 583-639, 2002). We also consider the problem of detecting an influential point concerning skewness using Bayes factors. Finally, concluding remarks are discussed.

Analysis of Bus Accident Severity Using K-Means Clustering Model and Ordered Logit Model (K-평균 군집모형 및 순서형 로짓모형을 이용한 버스 사고 심각도 유형 분석 측면부 사고를 중심으로)

  • Lee, Insik;Lee, Hyunmi;Jang, Jeong Ah;Yi, Yongju
    • Journal of Auto-vehicle Safety Association
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    • v.13 no.3
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    • pp.69-77
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    • 2021
  • Although accident data from the National Police Agency and insurance companies do not know the vehicle safety, the damage level information can be obtained from the data managed by the bus credit association or the bus company itself. So the accident severity was analyzed based on the side impact accidents using accident repair cost. K-means clustering analysis separated the cost of accident repair into 'minor', 'moderate', 'severe', and 'very severe'. In addition, the side impact accident severity was analyzed by using an ordered logit model. As a result, it is appeared that the longer the repair period, the greater the impact on the severity of the side impact accident. Also, it is appeared that the higher the number of collision points, the greater the impact on the severity of the side impact accident. In addition, oblique collisions of the angle of impact were derived to affect the severity of the accident less than right angle collisions. Finally, the absence of opponent vehicle and large commercial vehicles involved accidents were shown to have less impact on the side impact accident severity than passenger cars.

Analysis on the Satisfaction Factors of Housing Performance and Residential Environment of Public Housing in Seoul (서울시 공공임대주택 주택성능과 주거환경 만족도에 미치는 영향요인)

  • Sung, Jin-Uk;Nam, Jin
    • Journal of Korea Planning Association
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    • v.54 no.3
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    • pp.49-62
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    • 2019
  • In order to balance with supply policy, public housing management and operation policies have been implemented in terms of housing welfare, but citizens have not yet achieved the results that the citizens are experiencing. The purpose of this study is to analysis the residential satisfaction of the including the housing performance through the characteristics of the public housing residents in Seoul. The data used in this study is based on the survey data of public housing panel survey in Seoul (2016). The study method used ordered logistic regression analysis based on the fact that dependent variables appeared as ordered responses. Major research results are as follows. Firstly, housing performance and residential satisfaction may not match. Even though the satisfaction of housing area, type, and management fee is high, satisfaction with residential environment is low if commuting distance, the number of small libraries, and hospitals are small. Secondly, it showed different characteristics of residential environment factors among types of public housing. Rather than focusing on supply, customized supply is needed considering characteristics of public housing types. Thirdly, the policy for public housing needs to be realized by a fair policy on the residential environment. It is necessary to contribute to better housing stability as a customized policy considering the local residential environment.