• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1039-1047
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• 2014

An autoregressive model with normal errors is a natural model that attempts to fit time series data. More flexible models that include normal distribution as a special case are necessary because they can cover normality to non-normality models. The skewed exponential power distribution is a possible candidate for autoregressive models errors that may have tails lighter(platykurtic) or heavier(leptokurtic) than normal and skewness; in addition, the use of skewed exponential power distribution can reduce the influence of outliers and consequently increases the robustness of the analysis. We use SIR algorithm and grid method for an efficient Bayesian estimation.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.518-532
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• 2008

Broadcast scheme has been widely researched for efficient data delivery in the mobile environment because the downlink capacity of a mobile client is much greater than the uplink capacity, and the power of a mobile client is limited. In the proposed scheme, the index lets the client know when data items would be broadcasted and enables the client to minimize the tuning time and power consumption. Single channel index schemes are fit to flat broadcast that performs well when all the broadcasted data items are accessed with the same probability whereas the multi-disk broadcast scheme is proper when the data access distribution is skewed. The existing index schemes, however, cannot work on the Multi-disk broadcast scheme because they cannot point the replicating data items in a broadcast cycle. This paper proposes a Multi-disk Exponential Index (MDEI) which is a single channel index scheme fit to Multi-disk broadcast scheme. Because MDEI scheme organizes a separate index for each disk, it functions with multi-disk broadcast, resulting in a greater reduction of average access latency than that of other flat-broadcast index schemes when the data access distribution is skewed. The performance evaluation showed that MDEI has a good performance when data access distribution is skewed. MDEI has short average access latency and not much average tuning time when the data access distribution is skewed.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.837-847
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• 2012

Inverse Gaussian distribution is widely used in applications to analyze and model right-skewed data. To assess the appropriateness of the distribution prior to data analysis, Mudholkar and Tian (2002) proposed an entropy-based test of fit. The test is based on the entropy power fraction(EPF) index suggested by Gokhale (1983). The simulation results report that the power of the entropy-based test is superior compared to other goodness-of-fit tests; however, this observation is based on the small-scale simulation results on the standard exponential, Weibull W(1; 2) and lognormal LN(0:5; 1) distributions. A large-scale simulation should be performed against various alternative distributions to evaluate the power of the entropy-based test; however, the use of a theoretical method is more effective to investigate the powers. In this paper, utilizing the information discrimination(ID) index defined by Ehsan et al. (1995) as a mathematical tool, we scrutinize the power of the entropy-based test. The selected alternative distributions are the gamma, Weibull and lognormal distributions, which are widely used in data analysis as an alternative to inverse Gaussian distribution. The study results are provided and an illustrative example is analyzed.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.501-512
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• 2014

Modified cut-off sampling is widely used for highly skewed data. A serious drawback of modified cut-off sampling is the difficulty of adjustment of non-response in take-all stratum. Therefore, solutions of the problems of non-response in take-all stratum have been studied in various ways such as substitute of samples, imputation or re-weight method. In this paper, a new cut-off point based on minimizing MSE being used in exponential and power functions is suggested and it can be reduced the number of take-all stratum. We also investigate another cut-off point determination method with underlying distributions such as truncated log-normal and truncated gamma distributions. Finally we suggest the optimal cut-off point which has a minimum of take-all stratum size among suggested methods. Simulation studies are performed and Labor Survey data and simulated data are used for the case study.