Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Journal of the Korean Data and Information Science Society
Journal Basic Information
Journal DOI :
Korean Data and Information Science Society
Editor in Chief :
Volume & Issues
Volume 10, Issue 2 - Oct 1999
Volume 10, Issue 1 - Apr 1999
Selecting the target year
Comparison of Estimators of Dependence Related Parameter in Generalized Binomial Distribution
Moon, Myung-Sang ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 279~288
In many cases where the conventional binomial distribution fails to apply to real world data, it is mainly due to the lack of independence among Bernoulli trials. Several authors have proposed models that are useful when independence assumption is not satisfied. In this paper, one proposed model is adapted, and estimators of dependence related parameter that is crucial in defining that model are considered. Simulation is performed to compare two estimators(method of moment estimator and maximum likelihood estimator) of dependence related parameter, and conclusions are made.
Large Robust Designs for Generalized Linear Model
Kim, Young-Il ; Kahng, Myung-Wook ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 289~298
We consider a minimax approach to make a design robust to many types or uncertainty arising in reality when dealing with non-normal linear models. We try to build a design to protect against the worst case, i.e. to improve the "efficiency" of the worst situation that can happen. In this paper, we especially deal with the generalized linear model. It is a known fact that the generalized linear model is a universal approach, an extension of the normal linear regression model to cover other distributions. Therefore, the optimal design for the generalized linear model has very similar properties as the normal linear model except that it has some special characteristics. Uncertainties regarding the unknown parameters, link function, and the model structure are discussed. We show that the suggested approach is proven to be highly efficient and useful in practice. In the meantime, a computer algorithm is discussed and a conclusion follows.
Recurrence Relation and Characterization of The Rayleigh Distribution Using Order Statistics
Lee, In-Suk ; Kim, Sang-Moon ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 299~311
In this paper the single and product moments of order statistics of the doubly truncated Rayleigh distribution are studied. Some recurrence relations of order statistics are derived. Using order statistics, also characterization of the Rayleigh distribution are derived.
Asymptotic Distribution in Estimating a Population Size
Choi, Ki-Heon ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 313~318
Suppose that there is a population of hidden objects of which the total number N is unknown. From such data, we derive an asymptotic distribution.
Inferences for the Changepoint in Bivariate Zero-Inflated Poisson Model
Kim, Kyung-Moon ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 319~327
Zero-Inflated Poisson distributions have been widely used for defect-free products in manufacturing processes. It is very interesting to check the shift after the unknown changepoint. If the detectives are caused by the two different types of factor, we should use bivariate zero-inflated model. In this paper, likelihood ratio tests were used to detect the shift of changes after the changepoint. Some inferences for the parameters in this model were made.
Finite Population Prediction under Multiprocess Dynamic Generalized Linear Models
Kim, Dal-Ho ; Cha, Young-Joon ; Lee, Jae-Man ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 329~340
We consider a Bayesian forcasting method for the analysis of repeated surveys. It is assumed that the parameters of the superpopulation model at each time follow a stochastic model. We propose Bayesian prediction procedures for the finite population total under multiprocess dynamic generalized linear models. The multiprocess dynamic model offers a powerful framework for the modelling and analysis of time series which are subject to a abrupt changes in pattern. Some numerical studies are provided to illustrate the behavior of the proposed predictors.
Better Bootstrap Confidence Intervals for Process Incapability Index
Cho, Joong-Jae ; Han, Jeong-Hye ; Lee, In-Pyo ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 341~357
Greenwich and Jahr-Schaffrath(1995) considered a new process incapability index(PII)
, which modified the useful index
for detecting assignable causes. The new index
provides an uncontaminated separation between information concerning the process accuracy and precision while this kind of information separation is not available with the
index. In this paper, we will study about the index
based on the bootstrap. First, we will prove the consistency of bootstrap deriving the bootstrap asymptotic distribution for our index
. Moreover, with the consistency of bootstrap, we will construct six bootstrap confidence intervals and compare their performances. Some simulation results, comparison and analysis are provided. In particular, two STUD and ABC bootstrap methods perform significantly better.
A Study on Reasoning for Medical Expert Systems
Kim, Jin-Sang ; Shin, Yang-Kyu ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 359~367
We investigate a logical approach to represent medical knowledge, reason deductively and diagnostically. It is suggested that medical knowledge-bases can be formulated as a set of sentences stated in classical logic where each sentence reflects a doctor's knowledge about the human anatomy or his/her view of patient's symptoms. It is also suggested that a form of temporal reasoning can be captured within the same framework because each sentence can have a different truth value based on time. We apply our logical framework to formalize diagnostic reasoning, where the primary cause of illness is chosen among the set of minimal causation on the basis of abductive hypotheses. Most of our examples are given in the context of medical expert systems.
Outlier Detection in Growth Curve Model Using Mean-Shift Model
Shim, Kyu-Bark ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 369~385
For the growth curve model with arbitrary covariance structure, known as unstructured covariance matrix, the problems of detecting outliers are discussed in this paper. In order to detect outliers in the growth curve model, the likelihood ratio testing statistics in mean shift model is established and its distribution is derived. After we detected outliers in growth curve model, we test homo and/or hetero-geneous covariance matrices using PSR Quasi-Bayes Criterion. For illustration, one numerical example is discussed, which compares between before and after outlier deleting.
Goodness-of-fit tests based on Entropy Estimators
Kim, Jong-Tae ; Cha, Young-Jun ; Kim, Young-Hun ; Lee, Jae-Man ; Kang, Sang-Kil ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 387~395
The goal of this paper is to study of the entropy - based on goodness-of-fit tests with several parametric models. It is also to study the relationship of the Moran's test statistic on the view of entropy.
Simultaneous Confidence Regions for Spatial Autoregressive Spectral Densities
Ha, Eun-Ho ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 397~404
For two-dimensional causal spatial autoregressive processes, we propose and illustrate a method for determining asymptotic simultaneous confidence regions using Yule-Walker, unbiased Yule-Walker and least squres estimators. The spectral density for first-order spatial autoregressive model are looked at in more detail. Finite sample properties based on simulation study we also presented.
AMLE for the Rayleigh Distribution with Type-II Censoring
Kang, Suk-Bok ; Cho, Young-Suk ; Hwang, Kwang-Mo ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 405~413
By assuming a type-II censoring, we propose the approximate maximum likelihood estimators (AMLEs) of the location and the scale parameters of the two-parameter Rayleigh distribution and calculate the asymptotic variances and covariance of the AMLEs.
Tail Probability Approximations for the Ratio of two Independent Sequences of Random Variables
Cho, Dae-Hyeon ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 415~428
In this paper, we study the saddlepoint approximations for the ratio of two independent sequences of random variables. In Section 2, we review the saddlepoint approximation to the probability density function. In section 3, we derive an saddlepoint approximation formular for the tail probability by following Daniels'(1987) method. In Section 4, we represent a numerical example which shows that the errors are small even for small sample size.
Power Analysis for Normality Plots
Lee, Jae-Young ; Rhee, Seong-Won ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 429~436
We suggest test statistics for normality using Q-Q plot and P-P plot and obtain empirical quantities of these statistics. Also the power comparison with Shapiro-Wilk's W is conducted by Monte Carlo study.
Control Chart for Constant Hazard Rate
Lee, Jae-Man ; Cha, Young-Joon ; Hong, Yeon-Woong ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 437~444
We propose control charts for constant hazard rate by using the number of failures based on the non-placement(replacement) life test. Also we study the sensitivity of the control chart from the operating characteristic curve.
Assessing Cure Rates via Piecewise Gompertz model with Covariates
Chung, Dae-Hyun ; Won, Dong-Yu ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 445~455
We modify the Gompertz regression model for estimation of cure rates from pediatric clinical trials by assuming different hazard rates on the different periods. A treatment period may be divided by the stages of treatments under the different treatment arms. The piecewise Gompertz models provide an efficient method for estimation of the cure rates and a method for testing the difference of the treatment effects in the given interval.
Measurement of Association of Categorical Data Using The Overlapped Mosaic Plot : Dynamic Graphics Approach for
Yoon, Yeo-Chang ; Oh, Min-Gweon ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 457~464
In this paper, we propose an overlapped mosaic plot which proposed by Hartigan and Kleiner(1981) represents the counts in
contingency table directly by tiles whose area is proportional to the cell frequency. Overlapped mosaic plot provides some measurements of association including dynamic graphics for mosaic plots. Dynamic graphics for mosaic plots give some useful informations when one gets some measurements of association and selects a model, and current statistical software does not provide this feature. We can see the deviations between observation and estimate of independence from overlapped mosaic plot. This dynamic graphics give some useful informations how far this data are apart from independence.
Bootstrap Confidence Intervals for a One Parameter Model using Multinomial Sampling
Jeong, Hyeong-Chul ; Kim, Dae-Hak ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 465~472
We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.
Construction and Performance Test of a Supercomputing PC System using PC-clustering and Parallel Virtual Machine
Hong, Woo-Pyo ; Kim, Jong-Jae ; Oh, Kwang-Sik ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 473~483
We introduce a way to construct a supercomputing capable system with some networked PCs, running the Linux operating system and computing power comparable with expensive commercial workstations, and with the Parallel Virtual Machine (PVM) software which enables one to control the total CPUs and memories of the networked PCs. By benchmarking the system using a PVM parallel program, we find that the system's parallel efficiency is close to 90 %.
Development of Interest Rates Forecasting System Using the SAS/ETS
Lee, Jeong-Hyeong ; Chu, Min-Jeong ; Cho, Sin-Sup ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 485~500
The systematic forecast of interest rates with liberalization was on the rise to important problems in the money market. Liberalization and globalization of the money market produced a seriously change as a compatition among the money market. Profits of an organ of monetary circulation are, also, definitively influenced by a change of interest rates. Hence most of the organ of monetary circulation studied to a scientific and systematic analysis for deterministic factors which have an effect on interest rates and progress development of a forecasting model of interest rates. In this paper, we develope the forecasting system which has highly forecasting performance based on a number of time series models for interest rates and discuss practical use of this system.
Statistical Analysis on the Web Using PHP3
Hwang, Jin-Soo ; Uhm, Dae-Ho ;
Journal of the Korean Data and Information Science Society, volume 10, issue 2, 1999, Pages 501~510
We have seen a rapid development of multimedia intustry as computer evolves and the internet has changed our way of life dramatically in these days. There we several attempts to teach elementary statistics on the web but most of them are based on commercial products. The need for statistical data analysis and decision making based on those analysis is growing. In this article we try to show one way of reaching that goal by using a server side scripting language PHP3 toghether with extra graphical module and statistical distribution module on the web. We showed some elementary exploratory graphical data analysis and statistical inferences. There are plenty of room of improvements to make it a full blown statistical analysis tool on the web in the new future. All the programs and databases used in our article we public programs. The main engine PHP3 is included as an apache web server module so it is very light and fast. It will be much better when the PHP4(ZEND) will be officially out in terms of processing speed.