• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.593-610
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• 2015

Adaptive Rejection Sampling (ARS) method is a well-known random number generator to acquire a random sample from a probability distribution, and has the advantage of improving the proposal distribution during the sampling procedures, which update it closer to the target distribution. However, the use of ARS is limited since it can be used only for the target distribution in the form of the log-concave function, and thus various methods have been proposed to overcome such a limitation of ARS. In this paper, we attempt to compare five random number generators based on ARS in terms of adequacy and efficiency. Based on empirical analysis using simulations, we discuss their results and make a comparison of five ARS-based methods.

• Journal of the Korean earth science society
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• v.38 no.7
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• pp.511-521
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• 2017

This study analyzes Two-dimensional video disdrometer (2DVD) data while summer 2011-2012 in Daegu region and compares with Marshall and Palmer (MP) distribution to find out statistical characteristics and characteristics variability about drop size distribution (DSD) of Daegu region. As the characterize DSD of Daegu region, this study uses single moment parameters such as rainfall intensity (R), reflectivity factor (Z) and double moment parameters such as generalized characteristics number concentration ($N{_0}^{\prime}$) and generalized characteristics diameter ($D{_m}^{\prime}$). Also, this study makes an assumption that DSD function can be expressed as general gamma distribution. The results of analysis show that DSD of Daegu region has ${\log}_{10}N{_0}^{\prime}=2.37$, $D{_m}^{\prime}=1.04mm$, and c =2.37, ${\mu}=0.39$ on average. When the assumption of MP distribution is used, these figures then end up with the different characteristics; ${\log}_{10}N{_0}^{\prime}=2.27$, $D{_m}^{\prime}=0.9mm$, c =1, ${\mu}=1$ on average. The differences indicate liquid water content (LWC) of Daegu distribution is generally larger than MP distribution at equal Z. Second, DSD shape of Daegu distribution is concave upward. Other important facts are the characteristics of Daegu distribution change when Z changes. DSD shape of Daegu region changes concave downward (c =2.05~2.55, ${\mu}=0.33{\sim}0.77$) to cubic function-like shape (c =3.0, ${\mu}=-0.13{\sim}-0.33$) at Z > 45 dBZ. 35 dBZ ${\leq}$ Z > 45 dBZ group of Daegu distribution has characteristics similar to maritime cluster of diverse climate DSD study. However, Z > 45 dBZ group of Daegu distribution has a difference from the cluster.