• Title/Summary/Keyword: binomial data

Search Result 342, Processing Time 0.029 seconds

Sampling Based Approach for Combining Results from Binomial Experiments

  • Cho, Jang-Sik;Kim, Dal-Ho;Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
    • /
    • v.12 no.1
    • /
    • pp.1-9
    • /
    • 2001
  • In this paper, the problem of information related to I binomial experiments, each having a distinct probability of success ${\theta}_i$, i = 1,2, $\cdots$, I, is considered. Instead of using a standard exchangeable prior for ${\theta}\;=\;({\theta}_1,\;{\theta}_2,\;{\cdots},\;{\theta}_I)$, we con-sider a partition of the experiments and take the ${\theta}_i$'s belonging to the same partition subset to be exchangeable and the ${\theta}_i$'s belonging to distinct subsets to be independent. And we perform Gibbs sampler approach for Bayesian inference on $\theta$ conditional on a partition. Also we illustrate the methodology with a real data.

  • PDF

Maximum likelihood estimation for a mixture distribution (이항-퇴화 혼합분포의 최우추정법)

  • Hwang, Seonyeong;Sohn, Seung Hye;Oh, Changhyuck
    • Journal of the Korean Data and Information Science Society
    • /
    • v.26 no.2
    • /
    • pp.313-322
    • /
    • 2015
  • A mixture distribution of a discrete uniform or degenerated distribution and two binomial distribution is proposed and a method of obtaining the maximum likelihood estimates of the parameters is provided. For the proposed model simulation studies were conducted to see performance of the maximum likelihood estimates and a mixture of a degenerated distribution and two binomial distributions was applied to fit a lecture evaluation data to show a good result.

Safety Performance Functions for Central Business Districts Using a Zero-Inflated Model (영과잉을 고려한 중심상업지구 교통사고모형 개발에 관한 연구)

  • Lee, Sang Hyuk;Woo, Yong Han
    • International Journal of Highway Engineering
    • /
    • v.18 no.4
    • /
    • pp.83-92
    • /
    • 2016
  • PURPOSES : The purpose of this study was to develop safety performance functions (SPFs) that use zero-inflated negative binomial regression models for urban intersections in central business districts (CBDs), and to compare the statistical significance of developed models against that of regular negative binomial regression models. METHODS : To develop and analyze the SPFs of intersections in CBDs, data acquisition was conducted for dependent and independent variables in areas of study. We analyzed the SPFs using zero-inflated negative binomial regression model as well as regular negative binomial regression model. We then compared the results by analyzing the statistical significance of the models. RESULTS : SPFs were estimated for all accidents and injury accidents at intersections in CBDs in terms of variables such as AADT, Number of Lanes at Major Roads, Median Barriers, Right Turn with an Exclusive Turn Lane, Turning Guideline, and Front Signal. We also estimated the log-likelihood at convergence and the likelihood ratio of SPFs for comparing the zero-inflated model with the regular model. In he SPFs, estimated log-likelihood at convergence and the likelihood ratio of the zero-inflated model were at -836.736, 0.193 and -836.415, 0.195. Also estimated the log-likelihood at convergence and likelihood ratio of the regular model were at -843.547, 0.187 and -842.631, 0.189, respectively. These figures demonstrate that zero-inflated negative binomial regression models can better explain traffic accidents at intersections in CBDs. CONCLUSIONS : SPFs that use a zero-inflated negative binomial regression model demonstrate better statistical significance compared with those that use a regular negative binomial regression model.

A Study on Reliability Evaluation of Application Software using Binomial-Type Model (이항형 모형을 이용한 응용 소프트웨어 의 신뢰성 평가에 관한 연구)

  • 조성건;이상철
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.15 no.25
    • /
    • pp.53-62
    • /
    • 1992
  • Computer software users develop and utilize their application software by themselves since Processing methods are different by quantity and qualify of the information The developed model needs input data and error numbers generated during the testing phases. However. total error numbers of the existing model and each error time was needed as data for developing the new model. But, maximum likelihood estimation must be used to exponential model of binomial-type and estimating of parameters by using the searched data. Parameter estimation can be done with trial and error or simulation.

  • PDF

Development of an Overseas Real Estate Valuation Model Considering Changes in Population Structure

  • Gu, Seung-Hwan;Kim, Doo-Suk;Ping, Wang;Jang, Seong-Yong
    • Journal of Distribution Science
    • /
    • v.12 no.3
    • /
    • pp.65-73
    • /
    • 2014
  • Purpose - Aging and fewer economically active people have challenged the assumption of continuous population increases. A new real estate valuation methodology reflecting changes in population structure is thus needed. Research design, data, and methodology - The relationship between demographic change and changes in real estate prices is analyzed using ordinary least squares (OLS) to estimate the parameters, and a population structure change (PSC)-Binomial Option Model is developed to assess the volatility of the estimated parameters. Results based on Seoul and Shanghai data are compared. Results - Results of the DCF method indicate that investing in Seoul is better than investing in Shanghai, but the binomial option indicates the opposite. The PSC-binomial option model, reflecting changes in population structure, yields higher values (24.6 million won in Seoul and 43.3 million won in Shanghai) than those given by the binomial option model. Conclusions - This study indicates that applying changes in population structure to existing research, such as in the binomial option model, represents a more accurate real estate valuation method. Results demonstrate that the new model is more accurate than existing models such as the DCF or binomial option.

On the Privacy Preserving Mining Association Rules by using Randomization (연관규칙 마이닝에서 랜덤화를 이용한 프라이버시 보호 기법에 관한 연구)

  • Kang, Ju-Sung;Cho, Sung-Hoon;Yi, Ok-Yeon;Hong, Do-Won
    • The KIPS Transactions:PartC
    • /
    • v.14C no.5
    • /
    • pp.439-452
    • /
    • 2007
  • We study on the privacy preserving data mining, PPDM for short, by using randomization. The theoretical PPDM based on the secure multi-party computation techniques is not practical for its computational inefficiency. So we concentrate on a practical PPDM, especially randomization technique. We survey various privacy measures and study on the privacy preserving mining of association rules by using randomization. We propose a new randomization operator, binomial selector, for privacy preserving technique of association rule mining. A binomial selector is a special case of a select-a-size operator by Evfimievski et al.[3]. Moreover we present some simulation results of detecting an appropriate parameter for a binomial selector. The randomization by a so-called cut-and-paste method in [3] is not efficient and has high variances on recovered support values for large item-sets. Our randomization by a binomial selector make up for this defects of cut-and-paste method.

A new sample selection model for overdispersed count data (과대산포 가산자료의 새로운 표본선택모형)

  • Jo, Sung Eun;Zhao, Jun;Kim, Hyoung-Moon
    • The Korean Journal of Applied Statistics
    • /
    • v.31 no.6
    • /
    • pp.733-749
    • /
    • 2018
  • Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.

A Bayesian zero-inflated negative binomial regression model based on Pólya-Gamma latent variables with an application to pharmaceutical data (폴랴-감마 잠재변수에 기반한 베이지안 영과잉 음이항 회귀모형: 약학 자료에의 응용)

  • Seo, Gi Tae;Hwang, Beom Seuk
    • The Korean Journal of Applied Statistics
    • /
    • v.35 no.2
    • /
    • pp.311-325
    • /
    • 2022
  • For count responses, the situation of excess zeros often occurs in various research fields. Zero-inflated model is a common choice for modeling such count data. Bayesian inference for the zero-inflated model has long been recognized as a hard problem because the form of conditional posterior distribution is not in closed form. Recently, however, Pillow and Scott (2012) and Polson et al. (2013) proposed a Pólya-Gamma data-augmentation strategy for logistic and negative binomial models, facilitating Bayesian inference for the zero-inflated model. We apply Bayesian zero-inflated negative binomial regression model to longitudinal pharmaceutical data which have been previously analyzed by Min and Agresti (2005). To facilitate posterior sampling for longitudinal zero-inflated model, we use the Pólya-Gamma data-augmentation strategy.

Urban and Rural Roundabout Accident Occurrence Models (도시 및 지방 회전교차로 사고 발생 모형)

  • Beck, Tea Hun;Lim, Jin Kang;Park, Byung Ho
    • International Journal of Highway Engineering
    • /
    • v.17 no.5
    • /
    • pp.39-46
    • /
    • 2015
  • PURPOSES: The operational characteristics of roundabouts are generally influenced by location as well as traffic volume. The goal of this study is to develop urban and rural roundabout accident models and to discuss safety improvement guidelines based on the model. METHODS : To analyze accidents, count data models are utilized in this study. This study used accident data from 2010 to 2013 for 56 roundabouts collected from the Traffic Accident Analysis System (TASS) of Road Traffic Authority. Poisson and negative binomial regression models were developed for this study using NLOGIT 4.0. RESULTS : The main results are as follows. First, the hypotheses that there are distributional differences in the number of accidents and injuries/fatalities among rural and urban roundabouts were accepted. Second, Poisson and negative binomial regression accident models, which were all statistically significant, were developed. Seven independent variables, which were statistically significant, were adopted. Third, the common variable of models was evaluated to be traffic volume. CONCLUSIONS : This study developed two negative binomial roundabout accident models and suggested some accident reduction strategies. The results are expected to give some implications to the safety improvement of roundabout.

Recurrence Formula for the Central Moments of Number of Successes with n Poisson Trials

  • Moon, Myung-Sang
    • Journal of the Korean Data and Information Science Society
    • /
    • v.14 no.2
    • /
    • pp.385-391
    • /
    • 2003
  • A sequence of n Bernoulli trials which violates the constant success probability assumption is termed as "Poisson trials". In this paper, the recurrence formula for the r-th central moment of number of successes with n Poisson trials is derived. Romanovsky's method, based on the differentiation of characteristic function, is used in the derivation of recurrence formula for the central moments of conventional binomial distribution. Romanovsky's method is applied to that of Poisson trials in this paper. Some central moment calculation results are given to compare the central moments of Poisson trials with those of conventional binomial distribution.

  • PDF