• Journal of IKEEE
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• v.15 no.1
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• pp.70-75
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• 2011

Longitudinal recording has been the cornerstone of all two generations of magnetic recording systems, FDD and HDD. In recent, perpendicular recording has received much attention as promising technology for future high-density recording system Research into signal processing techniques is paramount for the issued storage system and is indispensable like longitudinal recording systems. This paper focuses on the performance evaluation of the various detectors under perpendicular recording system. Parameters for improving the their performance are examined for some detectors. Detectors considered in this work are the partial response maximum likelihood (PRML), noise-predictive maximum likelihood (NPML), fixed delay tree search with decision feedback (FDTS/DF), dual decision feedback equalizer (DDFE) and multilevel decision feedback equalizer (MDFE). Their performances are analyzed in terms of mean squared error (MSE) and noise power spectra, and similarity between recording channel and partial response (PR) channel.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.1-8
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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 Robin (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. A numerical example is also presented to illustrate the method.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.33-39
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• 2013

In the transformation of response variable in partial linear models outliers can cause a bad effect on estimating the transformation parameter, just as in the linear models. To solve this problem the processes of estimating transformation parameter and detecting outliers are needed, but have difficulties to be performed due to the arbitrariness of the nonparametric function included in the partial linear model. In this study, through the estimation of nonparametric function and outlier detection methods such as a sequential test and a maximum trimmed likelihood estimation, processes for transforming response variable robust to outliers in partial linear models are suggested. The proposed methods are verified and compared their effectiveness by simulation study and examples.

• The Korean Journal of Applied Statistics
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• v.31 no.4
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• pp.475-484
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• 2018

Gamma generalized linear models are useful for non-negative and skewed responses. However, these models have received less attention than Poisson and binomial generalized linear models. In particular, hypothesis testing for the significance of regression coefficients has not been thoroughly studied. In this paper we assess the performance of various test statistics for gamma generalized linear models based on numerical studies. Our results show that the likelihood ratio test and F-type test are generally recommended and that the partial deviance test should be avoided in practice.

• Journal of applied mathematics & informatics
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• v.5 no.1
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• pp.41-50
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• 1998

There are various notions of partial ordering between life-times of systems; stochastic ordering failure rate ordering and likeli-hood ration ordering. In this paper we show that for series systems with non i.i.d. exponential lifetimes of components standby redundancy at component level is better than that at system level in failure rate or-dering and likelihood ratio ordering. We also demonstrate that for 2-component parallel systems with i.i.d. exponential lifetimes of com-ponents standby system redundancy is better than standby component redundancy in failure rate ordering and likelihood ratio ordering.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.26-35
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• 2014

We consider multiple-input multiple-output decode-and-forward relay systems in Rayleigh fading channels under the partial channel state information (CSI) that the channel statistics of the source-relay (SR) link and the instantaneous CSI of the source-destination and relay-destination links are known at the destination. In this paper, we propose a new near maximum likelihood (near-ML) decoder with two-level pairwise error probability (near-ML-2PEP) which uses the average PEP instead of the exact PEP. Then, we theoretically prove that the near-ML and near-ML-2PEP decoders achieve the maximum diversity, which is confirmed by Monte Carlo simulations. Moreover, we show that the near-ML-2PEP decoder can also achieve the maximum diversity by substituting the average PEP with the values that represent the error performance of the SR link.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.533-542
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• 2002

In this paper, a covariate adjusted logrank test is considered for censored paired data under the Cox proportional hazard model. The proposed score test resembles the adjusted logrank test of Tsiatis, Rosner and Tritchler (1985), which is derived from the partial likelihood. The dependence structure for paired data is accommodated into the test statistic by using' sum of square type' variance estimators. Several weight functions are also considered, which produce a class of covariate adjusted weighted logrank tests. Asymptotic normality of the proposed test is established and simulation studies with moderate sample size show the proposed test works well, particularly when there are dependence structure between treatment and covariates.

• Journal of Applied Reliability
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• v.1 no.2
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• pp.149-163
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• 2001

We study the normality of the maximum partial likelihood estimators for the proportional hazard model with informative censored data. The proposed models cover the cases in which the times to a primary event may be informatively or randomly censored and the times to a secondary event may be randomly censored. To estimate the parameters and to check the normality of the parameters in the model, we adopt the partial likelihood and counting process to use the martingale central limit theorem. Simulation studies are performed to examine the normality of the MPLE's for the five cases in which they depend upon the proportions of randomly censored and informative censored data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7C
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• pp.642-646
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• 2005

We propose an improved partial response maximum likelihood (PRML) detector with the branch value compensation of Viterbi decoder for asymmetric high-density optical channel. Since the compensation value calculated by a survival path is applied to each branch metric, it reduces the detection errors by the asymmetric channel. The proposed PRML detection scheme improves the detection performance on the $2^{nd},\;3^{rd}\;and\;4^{th}$ order PR targets for asymmetric optical recording channel.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.239-263
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• 1998

In this paper, we consider a multistate survival model which incorporates covariates and contains two illness states and two death states. The underlying stochastic process is assumed to follow nonhomogeneous Markov process. The estimates of survival, transition and competing risks probabilities are given via the methods of partial likelihood and nonparametric maximum likelihood. Our discussion is based on the statistical theory of counting process. An illustration is given to the data of patients in a heart transplant program. The goodness of fit procedures are also discussed to check the adequacy of the model.