• Title/Summary/Keyword: discrete data

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Sample size calculations for clustered count data based on zero-inflated discrete Weibull regression models

  • Hanna Yoo
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.55-64
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    • 2024
  • In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

Submarine Diving Simulation Using a DEVS-HLA Interface based on the Combined Discrete Event and Discrete Time Simulation Model Architecture (이산 사건/이산 시간 혼합형 시뮬레이션 모델 구조 기반 DEVS-HLA 인터페이스를 이용한 잠수함의 잠항 시뮬레이션)

  • Cha, Ju-Hwan;Ha, Sol;Roh, Myung-Il;Lee, Kyu-Yeul
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.4
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    • pp.279-288
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    • 2010
  • In this paper, a DEVS(Discrete EVent Systems Specification)-HLA(High Level Architecture) interface was developed in order to perform the simulation using the combined discrete event and discrete time simulation model architecture in a distributed environment. The developed interface connects the combined simulation model with the HLA/RTI(Run-Time Infrastructure) which is an international standard middleware for distributed simulation. The interface consists of an interface model, a model interpreter, and a distributed environment interpreter. The interface model was defined by using the combined simulation architecture in order to easily connect the existing combined simulation model without modification with the HLA/RTI. The model interpreter takes charge of data transmission between the interface model and the combined simulation model. The distributed environment interpreter takes charge of data transmission between the interface model and the HLA/RTI. To evaluate the applicability of the developed interface, it was applied to the diving simulation of a submarine in a distributed environment. The result shows that a simulation result in a distributed environment using the interface is the same to the result in a single computing environment.

Variability of GRF Components between Increased Running Times during Prolonged Run (오래달리기 시 시간 경과에 따른 지면 반력 성분의 Variability)

  • Ryu, Ji-Seon
    • Korean Journal of Applied Biomechanics
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    • v.24 no.4
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    • pp.359-365
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    • 2014
  • A study was conducted to investigate the possible effects of fatigue which was resulted from increased running time on the stability during a prolonged run. The purposes of this study were twofold: first, to determine the discrete and non-linear variability of GRF (ground reaction force) components between running times to know the body stability, and second, to determine the pattern between discrete and non-linear variability. Nineteens healthy young adult males served in this study as subjects who ran at their preferred running speed. GRF data for twenty strides were collected at 5, 65, and 125 minutes during run. Variance coefficient and Lyapunov Exponent techniques on the GRF data were used to calculate variability index for each of the running time conditions. There were no difference between discrete variabilities of three components of GRF, but non-linear variability of the Fz component of GRF was decreased by increasing running time (p<.01). No relationship was found between discrete and non-linear variability.

ICAIM;An Improved CAIM Algorithm for Knowledge Discovery

  • Yaowapanee, Piriya;Pinngern, Ouen
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.2029-2032
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    • 2004
  • The quantity of data were rapidly increased recently and caused the data overwhelming. This led to be difficult in searching the required data. The method of eliminating redundant data was needed. One of the efficient methods was Knowledge Discovery in Database (KDD). Generally data can be separate into 2 cases, continuous data and discrete data. This paper describes algorithm that transforms continuous attributes into discrete ones. We present an Improved Class Attribute Interdependence Maximization (ICAIM), which designed to work with supervised data, for discretized process. The algorithm does not require user to predefine the number of intervals. ICAIM improved CAIM by using significant test to determine which interval should be merged to one interval. Our goal is to generate a minimal number of discrete intervals and improve accuracy for classified class. We used iris plant dataset (IRIS) to test this algorithm compare with CAIM algorithm.

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Bayesian Curve Clustering in Microarray

  • Lee, Kyeong-Eun;Mallick, Bani K.
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.04a
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    • pp.39-42
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    • 2006
  • We propose a Bayesian model-based approach using a mixture of Dirichlet processes model with discrete wavelet transform, for curve clustering in the microarray data with time-course gene expressions.

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Derivations of moments for discrete probability distributions using backward difference operators (후진 미분 연산자를 이용한 이산확률분포의 적률 유도)

  • Cho, Kil-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.3
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    • pp.505-513
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    • 2011
  • In this paper, we obtain the derivations of moments of discrete probability distributions by using the backward difference operators. Also, we presents such derivations for several well-known distributions; they are the binomial, Poisson, geometric, hypergeometric and negative hypergeometric distributions.

A Discrete Time Approximation Method using Bayesian Inference of Parameters of Weibull Distribution and Acceleration Parameters with Time-Varying Stresses (시변환 스트레스 조건에서의 와이블 분포의 모수 및 가속 모수에 대한 베이시안 추정을 사용하는 이산 시간 접근 방법)

  • Chung, In-Seung
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.1331-1336
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    • 2008
  • This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

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The study of discrete wavelet transform for the coding and the compression of the audio data (이산 웨이브렛 변환을 이용한 Audio 신호의 기호화 및 압축)

  • Baek, Han-Wook;Chung, Chin-Hyun
    • Proceedings of the KIEE Conference
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    • 1998.07g
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    • pp.2262-2264
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    • 1998
  • This paper propose a new method for the discrete signal : Discrete Wavelet Transform(DWT). This paper is a brief introduction to the DWT and applies the DWT coding for the audio data as an example. We can have a number of hint about the compression algorithm of multimedia resources and the high performance of transmission and storage.

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DISCRETE EVOLUTION EQUATIONS ON NETWORKS AND A UNIQUE IDENTIFIABILITY OF THEIR WEIGHTS

  • Chung, Soon-Yeong
    • Journal of the Korean Mathematical Society
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    • v.53 no.5
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    • pp.1133-1148
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    • 2016
  • In this paper, we first discuss a representation of solutions to the initial value problem and the initial-boundary value problem for discrete evolution equations $${\sum\limits^l_{n=0}}c_n{\partial}^n_tu(x,t)-{\rho}(x){\Delta}_{\omega}u(x,t)=H(x,t)$$, defined on networks, i.e. on weighted graphs. Secondly, we show that the weight of each link of networks can be uniquely identified by using their Dirichlet data and Neumann data on the boundary, under a monotonicity condition on their weights.

Modeling and Parameter Estimation of an Electrohydraulic Servo System by the Least Square Method (최소자승법에 의한 전기유압식 서보시스템의 모델링 및 파라미터 평가)

  • Roh, Hyoung-Woo;Song, Chang-Sup
    • Journal of the Korean Society for Precision Engineering
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    • v.17 no.10
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    • pp.125-131
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    • 2000
  • By using the test of signal error, model structure of an electrohydraulic servo system is determined. For determining parameter of the electrohydraulic servo system, using time discrete model of parametric method, parameters in time discrete model are searched by the least square method. By bilinear transform, we have found the model of electrohydraulic servo system in s domain. Afterwards, we have compared experimental data with simulation data by MATLAB having the identified parameter. As the result, experimental data is agreed with simulation data very well.

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