• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.45-53
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• 2003

The Zero-Inflated Poisson regression is a model for count data with exess zeros. When the reponse variables have excess zeros, it is not easy to apply the Poisson regression model. In this paper, we study and simulate the zero-inflated Poisson regression model. An real example was applied to this model. Regression parameters are estimated by using MLE's. We also compare the fitness of zero-inflated Poisson model with the Poisson regression and decision tree model.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.161-171
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• 2006

In this paper, we consider the random number generation method for multivariate Poisson distribution with specific covariance matrix. Random number generating method for the multivariate Poisson distribution is considered into two part, by first solving the linear equation to determine the univariate Poisson parameter, then convoluting independent univariate Poisson variates with appropriate expectations. We propose a numerical algorithm to solve the linear equation given the specific covariance matrix.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.247-255
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• 1998

In this paper, a new subset selection problem in the Poisson model is considered under the normal predictors. It turns out that the subset model has bigger valiance than that of the Poisson model with random predictors and this has been used to derive new subset selection method similar to Mallows'$C_p$.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.159-167
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• 1995

Considering special discrete distribution of exponential family as a sequence with respect to the points of support, the squence is unimodal in some sense. In this paper, we study under what condition the mixture of that discrete distribution with respect to a parameter is unimodal. We derive the maximal interval of the parameter in which each mixture of the discrete distribution such as Binomial and Poisson is always unimodal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2217-2222
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• 2011

In this paper, the relationship of potential and charge distribution in channel for double gate(DG) MOSFET has been derived from Poisson's equation using Gaussian function. The relationship of subthreshold swing and oxide thickness has been investigated according to variables of doping distribution using Gaussian function, i.e. projected range and standard projected deviation, The analytical potential distribution model has been derived from Poisson's equation, and subthreshold swing has been obtained from this model for the change of oxide thickness. The subthreshold swing has been defined as the derivative of gate voltage to drain current and is theoretically minimum of 60 mS/dec, and very important factor in digital application. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the relationship of subthreshold swing and oxide thickness have been analyzed according to the shape of doping distribution.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.1-12
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• 2006

The aim of this study is to analyse a survey data on the number of charitable donations using a mixture of two Poisson regression models. The survey was conducted in 2002 by Volunteer 21, an nonprofit organization, based on Koreans, who were older than 20. The mixture of two Poisson distributions is used to model the number of donations based on the empirical distribution of the data. The mixture of two Poisson distributions implies the whole population is subdivided into two groups, one with lesser number of donations and the other with larger number of donations. We fit the mixture of Poisson regression models on the number of donations to identify significant covariates. The expectation-maximization algorithm is employed to estimate the parameters. We computed 95% bootstrap confidence interval based on bias-corrected and accelerated method and used then for selecting significant explanatory variables. As a result, the income variable with four categories and the volunteering variable (1: experience of volunteering, 0: otherwise) turned out to be significant with the positive regression coefficients both in the lesser and the larger donation groups. However, the regression coefficients in the lesser donation group were larger than those in larger donation group.

• Journal of the Korean Data and Information Science Society
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• v.22 no.1
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• pp.29-35
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• 2011

In statistical process control, the primary method used to monitor the number of nonconformities is the c-chart. The conventional c-chart is based on the assumption that the occurrence of nonconformities in samples is well modeled by a Poisson distribution. When the Poisson assumption is not met, the X-chart is often used as an alternative charting scheme in practice. And CUSUM-chart is used when it is desirable to detect out of control situations very quickly because of sensitive to a small or gradual drift in the process. In this paper, I compare CUSUM-chart to X-chart for the Katz family covering equi-, under-, and over-dispersed distributions relative to the Poisson distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.2000-2006
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• 2011

In this paper, the drain induced barrier lowering(DIBL) for doping distribution in the channel has been analyzed for double gate MOSFET(DGMOSFET). The DGMOSFET is extensively been studing because of adventages to be able to reduce the short channel effects(SCEs) to occur in convensional MOSFET. DIBL is SCE known as reduction of threshold voltage due to variation of energy band by high drain voltage. This DIBL has been analyzed for structural parameter and variation of channel doping profile for DGMOSFET. For this object, The analytical model of Poisson equation has been derived from Gaussian doping distribution for DGMOSFET. To verify potential and DIBL models based on this analytical Poisson's equation, the results have been compared with those of the numerical Poisson's equation, and DIBL for DGMOSFET has been investigated using this models.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.6
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• pp.1338-1342
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• 2011

In this paper, threshold voltage characteristics have been analyzed as one of short channel effects occurred in double gate(DG)MOSFET to be next-generation devices. The Gaussian function to be nearly experimental distribution has been used as carrier distribution to solve Poisson's equation, and threshold voltage has been investigated according to projected range and standard projected deviation, variables of Gaussian function. The analytical potential distribution model has been derived from Poisson's equation, and threshold voltage has been obtained from this model. Since threshold voltage has been defined as gate voltage when surface potential is twice of Fermi potential, threshold voltage has been derived from analytical model of surface potential. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the threshold voltage characteristics have been considered according to the doping profile of DGMOSFET.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2621-2626
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• 2013

This paper has presented the potential distribution for asymmetric double gate(DG) MOSFET, and sloved Poisson equation to obtain the analytical solution of potential distribution. The symmetric DGMOSFET where both the front and the back gates are tied together is three terminal device and has the same current controllability for front and back gates. Meanwhile the asymmetric DGMOSFET is four terminal device and can separately determine current controllability for front and back gates. To approximate with experimental values, we have used the Gaussian function as doping distribution in Poisson equation. The potential distribution has been observed for gate bias voltage and gate oxide thickness and channel doping concentration of the asymmetric DGMOSFET. As a results, we know potential distribution is greatly changed for gate bias voltage and gate oxide thickness, especially for gate to increase gate oxide thickness. Also the potential distribution for source is changed greater than one of drain with increasing of channel doping concentration.