• Journal of the Korean Data and Information Science Society
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• v.8 no.2
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• pp.246-246
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• 1997

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.495-500
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• 2012

We consider a Bayesian test of independence in a two-way contingency table that has some zero cells. To do this, we take a three-stage hierarchical Bayesian model under each hypothesis. For prior, we use Dirichlet density to model the marginal cell and each cell probabilities. Our method does not require complicated computation such as a Metropolis-Hastings algorithm to draw samples from each posterior density of parameters. We draw samples using a Gibbs sampler with a grid method. For complicated posterior formulas, we apply the Monte-Carlo integration and the sampling important resampling algorithm. We compare the values of the Bayes factor with the results of a chi-square test and the likelihood ratio test.

• The Journal of the Korean dental association
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• v.54 no.11
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• pp.850-864
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• 2016

The Generalized Estimating Equations (GEE) approach is a widely used statistical method for analyzing longitudinal data and clustered data in clinical studies. In dentistry, due to multiple outcomes obtained from one patient, the outcomes produced from an individual patient are correlated with one another. This study focused on the basic ideas of GEE and introduced the types of covariance matrix and working correlation matrix. The quasi-likelihood information criterion (QIC) and quasi-likelihood information criterion approximation ($QIC_u$) were used to select the best working correlation matrix and the best fitting model for the correlated outcomes. The purpose of this study is to show a detailed process for the GEE analysis using SPSS software along with an orthodontic miniscrew example, and to help understand how to use GEE analysis in dental research.

• The Korean Journal of Applied Statistics
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• v.6 no.1
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• pp.41-52
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• 1993

In this paper we study numerical behavior of the adjustments for the variances of the pearson and deviance type dispersion statistics in two overdispersed mixture models; negative binomial and beta-binomial distribution. They are important families of an extended quasi-likelihood model which is very useful for the joint modelling of mean and dispersion. Comparisons are done for two types of dispersion statistics for various mean and dispersion parameters by simulation studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1219-1225
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• 2007

In this paper, we propose a new quasi-orthogonal space-time block code(QO-STBC) achieving full rate and full diversity for general QAM and quasi-static Rayleigh fading channels with four transmit antennas. This code possesses the quasi orthogonal property like the conventional minimum decoding complexity QO-STBC(MDC-QO-STBC), which allows independently a maximum likelihood(ML) decoding to only require joint detection of two real symbols. By computer simulation results, we show that the proposed code exhibits the identical BER performance with the existing MDC-QO-STBC. However, the proposed code has an advantage in the transceiver implementation since the original coding scheme may be modified so that increases of peak-to-average power ratio occur at only two transmit antennas, but the MDC-QO-STBC does at all of transmit antennas.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.761-770
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• 2012

We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1583-1591
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• 1998

In this paper, we consider the quasi maximum likelihood(quasi-ML) detector which uses antenna arrays in asynchronous time-varing channels. It is shown that the proposed quasi-ml detector can be regarded as a beamformer followed by a decorrelator: a method based on the eigendecomposition of the correlation matrix of the inverse-filtered signal is proposed to estimate the channel vectors. We also show that the proposed algorithm estimates the channel vector within small mismatch loss in severe propagation environment through computer simulations.

• Journal of information and communication convergence engineering
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• v.2 no.4
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• pp.228-232
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• 2004

This paper proposes an efficient detection algorithm, which is composed of an interference nulling-and cancelling-based detection algorithm and a maximum likelihood (ML) detection algorithm having reduced numbers of signal points to be tested, for the quasi-orthogonal space-time code with four transmit antennas. When high-level modulation schemes are employed, the algorithm enables the quasi-orthogonal code to achieve near ML performance with a significant reduction in the computational load.

• Speech Sciences
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• v.11 no.4
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• pp.75-88
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• 2004

In this paper, we propose a new approach to sequential linear regression adaptation of continuous density hidden Markov models (CDHMMs) based on transformation space model (TSM). The proposed TSM which characterizes the a priori knowledge of the training speakers associated with maximum likelihood linear regression (MLLR) matrix parameters is effectively described in terms of the latent variable models. The TSM provides various sources of information such as the correlation information, the prior distribution, and the prior knowledge of the regression parameters that are very useful for rapid adaptation. The quasi-Bayes (QB) estimation algorithm is formulated to incrementally update the hyperparameters of the TSM and regression matrices simultaneously. Experimental results showed that the proposed TSM approach is better than that of the conventional quasi-Bayes linear regression (QBLR) algorithm for a small amount of adaptation data.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.257-265
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• 2011

In this paper, a cooperative relaying protocol called soft-decision-and-forward (SDF) with multiple antennas in each node is introduced. SDF protocol exploits the soft decision source symbol values from the received signal at the relay node. For orthogonal transmission (OT), orthogonal codes including Alamouti code are used and for non-orthogonal transmission (NT), distributed space-time codes are designed by using a quasi-orthogonal space-time block code. The optimal maximum likelihood (ML) decoders for the proposed protocol with low decoding complexity are proposed. For OT, the ML decoders are derived as symbolwise decoders while for NT, the ML decoders are derived as pairwise decoders. It can be seen through simulations that SDF protocol outperforms AF protocol for both OT and NT.