• Title/Summary/Keyword: Alpha estimation

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A New Parameter Estimation Method for a Zipf-like Distribution for Geospatial Data Access

  • Li, Rui;Feng, Wei;Wang, Hao;Wu, Huayi
    • ETRI Journal
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    • v.36 no.1
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    • pp.134-140
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    • 2014
  • Many reports have shown that the access pattern for geospatial tiles follows Zipf's law and that its parameter ${\alpha}$ represents the access characteristics. However, visits to geospatial tiles have temporal and spatial popularities, and the ${\alpha}$-value changes as they change. We construct a mathematical model to simulate the user's access behavior by studying the attributes of frequently visited tile objects to determine parameter estimation algorithms. Because the least squares (LS) method in common use cannot obtain an exact ${\alpha}$-value and does not provide a suitable fit to data for frequently visited tiles, we present a new approach, which uses a moment method of estimation to obtain the value of ${\alpha}$ when ${\alpha}$ is close to 1. When ${\alpha}$ is further away from 1, the method uses the associated cache hit ratio for tile access and uses an LS method based on a critical cache size to estimate the value of ${\alpha}$. The decrease in the estimation error is presented and discussed in the section on experiment results. This new method, which provides a more accurate estimate of ${\alpha}$ than earlier methods, promises more effective prediction of requests for frequently accessed tiles for better caching and load balancing.

SEQUENTIAL INTERVAL ESTIMATION FOR THE EXPONENTIAL HAZARD RATE WHEN THE LOSS FUNCTION IS STRICTLY CONVEX

  • Jang, Yu Seon
    • Korean Journal of Mathematics
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    • v.21 no.4
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    • pp.429-437
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    • 2013
  • Let $X_1$, $X_2$, ${\cdots}$, $X_n$ be independent and identically distributed random variables having common exponential density with unknown mean ${\mu}$. In the sequential confidence interval estimation for the exponential hazard rate ${\theta}=1/{\mu}$, when the loss function is strictly convex, the following stopping rule is proposed with the half length d of prescribed confidence interval $I_n$ for the parameter ${\theta}$; ${\tau}$ = smallest integer n such that $n{\geq}z^2_{{\alpha}/2}\hat{\theta}^2/d^2+2$, where $\hat{\theta}=(n-1)\bar{X}{_n}^{-1}/n$ is the minimum risk estimator for ${\theta}$ and $z_{{\alpha}/2}$ is defined by $P({\mid}Z{\mid}{\leq}{\alpha}/2)=1-{\alpha}({\alpha}{\in}(0,1))$ Z ~ N(0, 1). For the confidence intervals $I_n$ which is required to satisfy $P({\theta}{\in}I_n){\geq}1-{\alpha}$. These estimated intervals $I_{\tau}$ have the asymptotic consistency of the sequential procedure; $$\lim_{d{\rightarrow}0}P({\theta}{\in}I_{\tau})=1-{\alpha}$$, where ${\alpha}{\in}(0,1)$ is given.

New Methods for Estimation of Time Delay and Time-Frequency Delay in Impulsive NOise Environment Using FNOM and MD Criterion (임펄스 잡음 환경 하에서 FNOM와 MD를 이용한 새로운 시지연 및 시간-주파수 지연 복합 추정 방법)

  • Lee, Jin;Jung, Jung-Kyun;Lee, Young-Seok;Kim, Sung-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.5
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    • pp.96-104
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    • 1997
  • In this paper, we proposed new methods for estimation of time delay and time-frequency delay in impulsive noise environment. The proposed methods are developed using the theory of ${\alpha}-stable$ distribution, including the fractional negative order moment(FNOM) and minimum dispersion(MD), which are formulated for the time delay estimation and the fractional negative order ambiguity function and complex minimum dispersion, which are difined for the joint estimation of time delay and frequency delay. Through simulation work, its performance was compared with various other algorithms. As a result, while the conventional approaches based on second-order statistics are only verified in Gaussian noise environent ($S{\alpha}S$ noise with ${\alpha}$=2) and also the recently proposed robust methods by Nikias[7] are verified only in limited impulse noise ($S{\alpha}S$ noise with the range of $1<{\alpha}{\le}2$), the methods proposed are able to estimate the time delay in Gaussian and any impulsive noise environments($S{\alpha}S$ noise with the range of $0<{\alpha}{\le}2$).

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Jensen's Alpha Estimation Models in Capital Asset Pricing Model

  • Phuoc, Le Tan
    • The Journal of Asian Finance, Economics and Business
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    • v.5 no.3
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    • pp.19-29
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    • 2018
  • This research examined the alternatives of Jensen's alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

SOM Matting for Alpha Estimation of Object in a Digital Image (디지털 영상 객체의 불투명도 추정을 위한 SOM Matting)

  • Park, Hyun-Jun;Cha, Eui-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.1981-1986
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    • 2009
  • This paper presents new matting techniques. The matting is an alpha estimation technique of object in an image. We can extract the object in an image naturally using the matting technique. The proposed algorithms begin by segmenting an image into three regions: definitely foreground, definitely background, and unknown. Then we estimate foreground, background, and alpha for all pixels in the unknown region. The proposed algorithms learn the definitely foreground and definitely background using self-organizing map(SOM), and estimate an alpha value of each pixel in the unknown region using SOM learning result. SOM matting is distinguished between global SOM matting and local SOM matting by learning method. Experiment results show the proposed algorithms can extract the object in an image.

Probabilistic Safety Assessment of Nuclear Power Plants Using Alpha Factor Method for Common Cause Failure (알파모수 공통원인고장 평가 기법을 활용한 원자력발전소 안전성 평가)

  • Hwang, Seok-Won
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.10 no.1
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    • pp.51-55
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    • 2014
  • Based on the results of Probabilistic Safety Assessment(PSA) for a Nuclear Power Plant (NPP), Common Cause Failure(CCF) events have been recognized as one of the main contributors to the risk. Also, the CCF data and estimation method used in domestic PSA models have been pointed out as an issue with respect to the quality. The existing method of MGL and non-staggered testing even widely used were considered conservative in estimating the safety and had a limited capability in uncertainty analyses. Therefore, this paper presents the CCF estimation using a new generic data source and Alpha factor method. The analyses showed that Alpha factor and staggered method are effective in estimating the CCF contribution and risk insights of reference plant. This method will be a common bases for the optimization of new design for the construction plants as well as for the updating of safety assessment on the operating nuclear power plants.

Rotor Position and Speed Estimation of Interior Permanent Magnet Synchronous Motor using Unscented Kalman Filter

  • An, Lu;Hameyer, Kay
    • Journal of international Conference on Electrical Machines and Systems
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    • v.3 no.4
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    • pp.458-464
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    • 2014
  • This paper proposes the rotor position and rotor speed estimation for an interior permanent magnet synchronous machines (IPMSM) using Unscented Kalman Filter (UKF) in alpha-beta coordinate system. Conventional algorithms using UKF are based on the simple observer model of IPMSM in d-q coordinate system. Rotor acceleration is neglected within the sampling step. An expansion of the observer model in an alpha-beta coordinate system with the consideration of the rotor speed variation provides the improved rotor position and speed estimation. The results show good stability concerning the expansion of observer model for the IPMSM.

Graphical Estimation of the Parameters of the Stable Laws

  • Paulson, Albert-S.;Won, Hyung-Gyoo
    • Management Science and Financial Engineering
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    • v.2 no.1
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    • pp.103-122
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    • 1996
  • This paper presents an easily used graphical procedure for simultaneous estimation of the index, skewness, scale, and location parameters of the stable laws. First, the index $\alpha$ and skewness $\beta$ are estimated through the joint use of a tail length statistic $\widetilde{K_t}$ and a skewness statistic $\widetilde{K_s}$, both of which are functions of order statistics. Next, the function of order statistics needed for estimation of scale $\sigma$ and location $\mu$ are determined from a nomogram indexed on the estimates of $\alpha$ and $\beta$. Some applications and examples are provided.

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Nonparametric empirical bayes estimation of a distribution function with respect to dirichlet process prior in case of the non-identical components (분포함수의 추정및 응용에 관한연구(Dirichlet Process에 의한 비모수 결정이론을 중심으로))

  • 정인하
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.173-181
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    • 1993
  • Nonparametric empirical Bayes estimation of a distribution function with respect to dirichlet process prior is considered when sample sizes are varying from component to component. Zehnwirth's estimate of $\alpha$(R) is modified to be used in our empirical Bayes problem with non-identical components.

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Time delay estimation algorithm for measurement of muscle fiber conduction velocity (근섬유 전도 속도 측정을 위한 시지연 추정 알고리즘)

  • Jung, Jung-Gyun;Lee, Jin;Lee, Young-Seok;Kim, Deok-Young;Kim, Sung-Hwan
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1635-1638
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    • 1997
  • A measurement of conduction veloctiy of the action potentials along the muscle fibres has been applied to various diagnosis. When we measure muscle fiber conduction velocity, it occurs that not only change of conduction velocity but alos inclusion of mipulse component by physiological and experimental reason. So, robuster time delay estimation algorithm than general methods[1] is needed to find correct time delay form these signals. In this paper we, propose new time delay estimation algorithms, robust in impulsive noise, by using characteristic of .alpha.-stable distribution whcih defines impulsive noise well. Then we apply proposed algorthms to measure muscle fiber conduction velocity and compare them with other studies.

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