• Journal of Multimedia Information System
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• v.8 no.1
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• pp.31-34
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• 2021

The classical HMM is defined by a parameter triple �� = (��, A, B), where each parameter represents a collection of probability distributions: initial state, state transition and output distributions in order. This paper proposes a new stationary parameter e = (e1, e2, …, eN) where N is the number of states and et = P(|xt = i, y) for describing how an input pattern y ends in state xt = i at time t followed by nothing. It is often said that all is well that ends well. We argue here that all should end well. The paper sets the framework for the theory and presents an efficient inference and training algorithms based on dynamic programming and expectation-maximization. The proposed model is applicable to analyzing any sequential data with two or more finite segmental patterns are concatenated, each forming a context to its neighbors. Experiments on online Hangul handwriting characters have proven the effect of the proposed augmentation in terms of highly intuitive segmentation as well as recognition performance and 13.2% error rate reduction.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.451-456
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• 1997

Temperature distribution measurements in the mockup apparatus of reactor vessel were performed to determine the effective thermal conductivity of porous media with different geometry and to obtain the experimental data for the heat transfer processes by natural convection occurring in the air duct. The temperature distributions at four separated sections with different arrangements of porous media have different slopes according to the geometrical configuration. From the measured temperature distribution, effective thermal conductivity have been derived using the least square fitting method. The test at air duct was performed to the high heat removal at 3.4kW/$m^2$ by the natural convection from the outer wall to the air. And also the temperature distributions in the air duct agree well with the 1/7th power-law turbulent temperature distribution. The obtained heat transfer data have been compared with the Shin's and Sieger's correlations.

• Communications for Statistical Applications and Methods
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• v.30 no.2
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• pp.191-213
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• 2023

Unit distributions are frequently used in probability theory and statistics to depict meaningful variables having values between zero and one. Using convenient transformation, the unit inverse exponentiated weibull (UIEW) distribution, which is equally useful for modelling data on the unit interval, is proposed in this study. Quantile function, moments, incomplete moments, uncertainty measures, stochastic ordering, and stress-strength reliability are among the statistical properties provided for this distribution. To estimate the parameters associated to the recommended distribution, well-known estimation techniques including maximum likelihood, maximum product of spacings, least squares, weighted least squares, Cramer von Mises, Anderson-Darling, and Bayesian are utilised. Using simulated data, we compare how well the various estimators perform. According to the simulated outputs, the maximum product of spacing estimates has lower values of accuracy measures than alternative estimates in majority of situations. For two real datasets, the proposed model outperforms the beta, Kumaraswamy, unit Gompartz, unit Lomax and complementary unit weibull distributions based on various comparative indicators.

• Journal of the Korean Data and Information Science Society
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• v.20 no.2
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• pp.261-272
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• 2009

Kolmogorov-Smirnov (K-S) statistic has been widely used for testing homogeneity of two distributions in the credit rating models. Joseph (2005) used K-S statistic to obtain validation criteria which is most well-known. There are other homogeneity test statistics such as the Cramer-von Mises, Anderson-Darling, and Watson statistics. In this paper, these statistics are introduced and applied to obtain criterion of these statistics by extending Joseph (2005)'s work. Another set of alternative criterion is suggested according to various sample sizes, type a error rates, and the ratios of bads and goods by using the simulated data under the similar situation as real credit rating data. We compare and explore among Joseph's criteria and two sets of the proposed criterion and discuss their applications.

• Nuclear Engineering and Technology
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• v.32 no.4
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• pp.361-371
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• 2000

The 123Te(p,n)123I, 124Te(p,n)124I and 124Te(p,2n)123I reactions, among the many reaction channels opened, are the major reactions under consideration from a diagnostic purpose because reaction residuals as the gamma emitters are used for most radiophamaceutical applications involving radioiodine. Based on the available experimental data, the absorption cross sections and elastic scattering angular distributions of the proton-induced nuclear reaction on Te isotopes below 60 MeV are calculated using the optical model code APMNK. The transmission coefficients of neutron, proton, deuteron, trition and alpha particles are calculated by CUNF code and are fed into the GNASH code. By adjusting level density parameters and the pair correction values of some reaction channels, as well as the composite nucleus state density constants of the pre-equilibrium model, the production cross sections and energy-angle correlated spectra of the secondary light particles, as well as production cross sections and energy distributions of heavy recoils and gamma rays are calculated by the statistical plus pre-equilibrium model code GNASH. The calculated results are analysed and compared with the experimental data taken from the EXFOR. The optimized global optical model parameters give overall agreement with the experimental data over both the entire energy range and all tellurium isotopes.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.203-213
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• 2017

We study estimation and inference of joint conditional distributions of bivariate longitudinal outcomes using regression models and copulas. We consider a class of time-varying transformation models and combine the two marginal models using Gaussian copulas to estimate the joint models. Our models and estimation method can be applied in many situations where the conditional mean-based models are inadequate. Gaussian copulas combined with time-varying transformation models may allow convenient and easy-to-interpret modeling for the joint conditional distributions for bivariate longitudinal data. We apply our method to an epidemiological study of repeatedly measured bivariate cholesterol data.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.387-392
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.431-443
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• 2019

Goodness-of-fit techniques are an important topic in statistical analysis. Censored data occur frequently in survival experiments; therefore, many studies are conducted when data are censored. In this paper we mainly consider test statistics based on the empirical distribution function (EDF) to test normal distributions with unknown location and scale parameters when data are randomly censored. The most famous EDF test statistic is the Kolmogorov-Smirnov; in addition, the quadratic statistics such as the $Cram{\acute{e}}r-von$ Mises and the Anderson-Darling statistic are well known. The $Cram{\acute{e}}r-von$ Mises statistic is generalized to randomly censored cases by Koziol and Green (Biometrika, 63, 465-474, 1976). In this paper, we generalize the Anderson-Darling statistic to randomly censored data using the Kaplan-Meier estimator as it was done by Koziol and Green. A simulation study is conducted under a particular censorship model proposed by Koziol and Green. Through a simulation study, the generalized Anderson-Darling statistic shows the best power against almost all alternatives considered among the three EDF statistics we take into account.

• Journal of the Korean Physical Society
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• v.80
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• pp.953-963
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• 2022

Post-neutron emission fission product mass distributions are calculated by using pre-neutron emission fission product yields (FPYs) and neutron multiplicity. A semi-empirical model is used to calculate the pre-neutron FPY, first. Then the neutron multiplicity for each fission fragment mass is used to convert the pre-neutron FPY to the post-neutron FPY. In doing so, assumptions are made for the probability for a pre-emission fission fragment with a mass number A^* to decay to a post-emission fragment with a mass number A. The resulting post-neutron FPYs are compared with the data available. The systems where the experimental data of not only the pre- and post-neutron FPY but also neutron multiplicity are available are the thermal neutron-induced fission of ²³³U, ²³⁵U and ²³⁹Pu. Thus, we applied the model calculations to these systems and compared the calculation results with those from the GEF and the data from the ENDF and the EXFOR libraries. Both the pre- and post-neutron fission product mass distributions calculated by using the semi-empirical model and the neutron multiplicity reproduce the overall features of the experimental data.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.401-410
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Rubin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood. Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method.