• Title/Summary/Keyword: long-tail distribution

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POWER TAIL ASYMPTOTIC RESULTS OF A DISCRETE TIME QUEUE WITH LONG RANGE DEPENDENT INPUT

  • Hwang, Gang-Uk;Sohraby, Khosrow
    • Journal of the Korean Mathematical Society
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    • v.40 no.1
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    • pp.87-107
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    • 2003
  • In this paper, we consider a discrete time queueing system fed by a superposition of an ON and OFF source with heavy tail ON periods and geometric OFF periods and a D-BMAP (Discrete Batch Markovian Arrival Process). We study the tail behavior of the queue length distribution and both infinite and finite buffer systems are considered. In the infinite buffer case, we show that the asymptotic tail behavior of the queue length of the system is equivalent to that of the same queueing system with the D-BMAP being replaced by a batch renewal process. In the finite buffer case (of buffer size K), we derive upper and lower bounds of the asymptotic behavior of the loss probability as $K\;\longrightarrow\;\infty$.

Review of Application Models According to the Classification of Asymptotic Tail Distribution (근사 꼬리분포의 유형별 적용 모형 고찰)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2010.11a
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    • pp.35-39
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    • 2010
  • The research classifies three types of asymptotic tail distributions such as long(heavy, thick) tailed distribution, medium tailed distribution and short(light, thin) tailed distribution. The extreme value distributions(EVD) classified in this paper can be used in SPC(Statistical Process Control) control chart and reliability engineering.

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CLOSURE PROPERTY AND TAIL PROBABILITY ASYMPTOTICS FOR RANDOMLY WEIGHTED SUMS OF DEPENDENT RANDOM VARIABLES WITH HEAVY TAILS

  • Dindiene, Lina;Leipus, Remigijus;Siaulys, Jonas
    • Journal of the Korean Mathematical Society
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    • v.54 no.6
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    • pp.1879-1903
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    • 2017
  • In this paper we study the closure property and probability tail asymptotics for randomly weighted sums $S^{\Theta}_n={\Theta}_1X_1+{\cdots}+{\Theta}_nX_n$ for long-tailed random variables $X_1,{\ldots},X_n$ and positive bounded random weights ${\Theta}_1,{\ldots},{\Theta}_n$ under similar dependence structure as in [26]. In particular, we study the case where the distribution of random vector ($X_1,{\ldots},X_n$) is generated by an absolutely continuous copula.

On Tail Probabilities of Continuous Probability Distributions with Heavy Tails (두꺼운 꼬리를 갖는 연속 확률분포들의 꼬리 확률에 관하여)

  • Yun, Seokhoon
    • The Korean Journal of Applied Statistics
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    • v.26 no.5
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    • pp.759-766
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    • 2013
  • The paper examines several classes of probability distributions with heavy tails. An (asymptotic) expression for tail probability needs to be known to understand which class a given probability distribution belongs to. It is usually not easy to get expressions for tail probabilities since most absolutely continuous probability distributions are specified by probability density functions and not by distribution functions. The paper proposes a method to obtain asymptotic expressions for tail probabilities using only probability density functions. Some examples are given to illustrate the proposed method.

A Study of a Method for Maintaining Accuracy Uniformity When Using Long-tailed Dataset (불균형 데이터세트 학습에서 정확도 균일화를 위한 학습 방법에 관한 연구)

  • Geun-pyo Park;XinYu Piao;Jong-Kook Kim
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.05a
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    • pp.585-587
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    • 2023
  • Long-tailed datasets have an imbalanced distribution because they consist of a different number of data samples for each class. However, there are problems of the performance degradation in tail-classes and class-accuracy imbalance for all classes. To address these problems, this paper suggests a learning method for training of long-tailed dataset. The proposed method uses and combines two methods; one is a resampling method to generate a uniform mini-batch to prevent the performance degradation in tail-classes, and the other is a reweighting method to address the accuracy imbalance problem. The purpose of our proposed method is to train the learning models to have uniform accuracy for each class in a long-tailed dataset.

Estimation and Comparative Analysis on the Distribution Functions of Air and Water Temperatures in Korean Coastal Seas (우리나라 연안의 기온과 수온 분포함수 추정 및 비교평가)

  • Cho, Hong-Yeon;Jeong, Shin-Taek
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.28 no.3
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    • pp.171-176
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    • 2016
  • The distribution shapes of air and water temperatures are basic and essential information, which determine the frequency patterns of their occurrence. It is also very useful to understand the changes in long-term air and water temperatures with respect to climate change. The typical distribution shapes of air and water temperatures cannot be well fitted using widely used/accepted normal distributions because their shapes show multimodal distributions. In this study, Gaussian mixture distributions and kernel distributions are suggested as the more suitable models to fit their distribution shapes. Based on the results, the tail shape exhibits different patterns. The tail is long in higher temperature regions of water temperature distribution and in lower temperature regions of air temperature distribution. These types of shape comparisons can be useful to identify the patterns of long-term air and water temperature changes and the relationship between air and water temperatures. It is nearly impossible to identify change patterns using only mean-temperatures and normal distributions.

Time Series Modelling of Air Quality in Korea: Long Range Dependence or Changes in Mean? (한국의 미세먼지 시계열 분석: 장기종속 시계열 혹은 비정상 평균변화모형?)

  • Baek, Changryong
    • The Korean Journal of Applied Statistics
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    • v.26 no.6
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    • pp.987-998
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    • 2013
  • This paper considers the statistical characteristics on the air quality (PM10) of Korea collected hourly in 2011. PM10 in Korea exhibits very strong correlations even for higher lags, namely, long range dependence. It is power-law tailed in marginal distribution, and generalized Pareto distribution successfully captures the thicker tail than log-normal distribution. However, slowly decaying autocorrelations may confuse practitioners since a non-stationary model (such as changes in mean) can produce spurious long term correlations for finite samples. We conduct a statistical testing procedure to distinguish two models and argue that the high persistency can be explained by non-stationary changes in mean model rather than long range dependent time series models.

Numerical study of propeller boss cap fins on propeller performance for Thai Long-Tail Boat

  • Kaewkhiaw, Prachakon
    • Ocean Systems Engineering
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    • v.11 no.4
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    • pp.373-392
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    • 2021
  • The present paper purposes a numerical evaluation of the Thai Long-Tail Boat propeller (TLTBP) performance by without and with propeller boss cap fins (PBCF) in full-scale operating straight shaft condition in the first. Next, those are applied to inclined shaft conditions. The actual TLTBP has defined an inclined shaft propeller including the high rotational speed, therefore vortex from the propeller boss and boss cap (hub vortex) have been generated very much. The PBCF designs are considered to weaken of vortex behind the propeller boss which makes the saving energy for the propulsion systems. The blade sections of PBCF developed from the original TLTBP blade shape. The integrative for the TLTBP and the PBCF is analyzed to increase the performance using computational fluid dynamics (CFD). The computational results of propeller performance are thoroughly compared between without and with PBCF. Moreover, the effects of each PBCF component are computed to influence the TLTBP performance. The fluid flows around the propeller blades, propeller boss, boss cap, and vortex have been investigated in terms of pressure distribution and wake-fields to verify the increasing efficiency of propulsion systems.

Generating and Controlling an Interlinking Network of Technical Terms to Enhance Data Utilization (데이터 활용률 제고를 위한 기술 용어의 상호 네트워크 생성과 통제)

  • Jeong, Do-Heon
    • Journal of the Korean Society for information Management
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    • v.35 no.1
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    • pp.157-182
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    • 2018
  • As data management and processing techniques have been developed rapidly in the era of big data, nowadays a lot of business companies and researchers have been interested in long tail data which were ignored in the past. This study proposes methods for generating and controlling a network of technical terms based on text mining technique to enhance data utilization in the distribution of long tail theory. Especially, an edit distance technique of text mining has given us efficient methods to automatically create an interlinking network of technical terms in the scholarly field. We have also used linked open data system to gather experimental data to improve data utilization and proposed effective methods to use data of LOD systems and algorithm to recognize patterns of terms. Finally, the performance evaluation test of the network of technical terms has shown that the proposed methods were useful to enhance the rate of data utilization.

Fluid Queueing Model with Fractional Brownian Input

  • Lee, Jiyeon
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.649-663
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    • 2002
  • We consider an unlimited fluid queueing model which has Fractional Brownian motion(FBM) as an input and a single server of constant service rate. By using the result of Duffield and O'Connell(6), we investigate the asymptotic tail-distribution of the stationary work-load. When there are multiple homogeneous FBM inputs, the workload distribution is similar to that of the queue with one FBM input; whereas for the heterogeneous sources the asymptotic work-load distributions is dominated by the source with the largest Hurst parameter.