• Title/Summary/Keyword: Asymptotic variance

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A new test of exponentiality against NDVRL

  • Hassan, M.KH.
    • International Journal of Reliability and Applications
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    • v.16 no.2
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    • pp.123-133
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    • 2015
  • In this paper, the problem of testing exponentiality against net decreasing variance residual lifetime (NDVRL) classes of life distributions is investigated. For this property a nonparametric test is presented based on kernel method. The test is presented for complete and right censored data. Furthermore, Pitman's asymptotic relative efficiency (PARE) is discussed to assess the performance of the test with respect to other tests. Selected critical values are tabulated. Some numerical simulations on the power estimates are presented for proposed test. Finally, numerical examples are presented for the purpose of illustrating our test.

THE PRICING OF VULNERABLE OPTIONS UNDER A CONSTANT ELASTICITY OF VARIANCE MODEL

  • U, Junhui;Kim, Donghyun;Yoon, Ji-Hun
    • Journal of the Chungcheong Mathematical Society
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    • v.33 no.2
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    • pp.181-195
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    • 2020
  • This paper suggests the price of vulnerable European option under a constant elasticity of variance model by using asymptotic analysis technique and obtains the approximated solution of the option price. Finally, we illustrate an accuracy of the vulnerable option price so that the approximate solution is well-defined.

SEQUENTIAL CONFIDENCE INTERVALS WITH ${\beta}-PROTECTION$ IN A NORMAL DISTRIBUTION HAVING EQUAL MEAN AND VARIANCE

  • Kim, Sung-Kyun;Kim, Sung-Lai;Lee, Young-Whan
    • Journal of applied mathematics & informatics
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    • v.23 no.1_2
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    • pp.479-488
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    • 2007
  • A sequential procedure is proposed in order to construct one-sided confidence intervals for a normal mean with guaranteed coverage probability and ${\beta}-protection$ when the normal mean and variance are identical. First-order asymptotic properties on the sequential sample size are found. The derived results hold with uniformity in the total parameter space or its subsets.

Nonparametric detection algorithm of discontinuity points in the variance function

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.669-678
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    • 2007
  • An algorithm to detect the number of discontinuity points of the variance function in regression model is proposed. The proposed algorithm is based on the left and right one-sided kernel estimators of the second moment function and test statistics of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size. The finite sample performance is illustrated by simulated example.

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Asymptotic Properties of the Disturbance Variance Estimator in a Spatial Panel Data Regression Model with a Measurement Error Component

  • Lee, Jae-Jun
    • Communications for Statistical Applications and Methods
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    • v.17 no.3
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    • pp.349-356
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    • 2010
  • The ordinary least squares based estimator of the disturbance variance in a regression model for spatial panel data is shown to be asymptotically unbiased and weakly consistent in the context of SAR(1), SMA(1) and SARMA(1,1)-disturbances when there is measurement error in the regressor matrix.

Consistency of the Periodogram When the Long-Run Variance is Degenerate

  • Lee, Jin
    • Communications for Statistical Applications and Methods
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    • v.19 no.2
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    • pp.287-292
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    • 2012
  • Sample periodogram is widely known as an inconsistent estimator for true spectral density. We show that it becomes consistent when the true spectrum at the zero frequency (often known as long-run variance) equals zero. Asymptotic results for consistency of the periodogram as well as the rate of convergence are formally derived.

Asymptotic Properties of the Stopping Times in a Certain Sequential Procedure

  • Kim, Sung-Lai
    • Journal of the Korean Statistical Society
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    • v.24 no.2
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    • pp.337-347
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    • 1995
  • In the problem of some sequential estimation, the stopping times may be written in the form $N(c) = inf{n \geq n_0; n \geq c^2 S^2_n/\delta^2 (\bar{X}_n)}$ where ${s^2_n}$ and ${\bar{X}_n}$ are the sequences of sample variance and sample mean of the independently and identically distributed (i.i.d.) random variables with distribution $F_{\theta}(x), \theta \in \Theta$, respectively, and $\delta$ is either constant or any given positive real valued function. We obtain some asymptotic normality and asymptotic expectation of the N(c) in various limiting situations. Specially, uniform asymptotic normality and uniform asymptotic expectation of the N(c) are given.

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A Study on Kernel Type Discontinuity Point Estimations

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.4
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    • pp.929-937
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    • 2003
  • Kernel type estimations of discontinuity point at an unknown location in regression function or its derivatives have been developed. It is known that the discontinuity point estimator based on $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a zero value at the point 0 makes a poor asymptotic behavior. Further, the asymptotic variance of $Gasser-M\ddot{u}ller$ regression estimator in the random design case is 1.5 times larger that the one in the corresponding fixed design case, while those two are identical for the local polynomial regression estimator. Although $Gasser-M\ddot{u}ller$ regression estimator with a one-sided kernel function which has a non-zero value at the point 0 for the modification is used, computer simulation show that this phenomenon is also appeared in the discontinuity point estimation.

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Testing of a discontinuity point in the log-variance function based on likelihood (가능도함수를 이용한 로그분산함수의 불연속점 검정)

  • Huh, Jib
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.1
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    • pp.1-9
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    • 2009
  • Let us consider that the variance function in regression model has a discontinuity/change point at unknown location. Yu and Jones (2004) proposed the local polynomial fit to estimate the log-variance function which break the positivity of the variance. Using the local polynomial fit, Huh (2008) estimate the discontinuity point of the log-variance function. We propose a test for the existence of a discontinuity point in the log-variance function with the estimated jump size in Huh (2008). The proposed method is based on the asymptotic distribution of the estimated jump size. Numerical works demonstrate the performance of the method.

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On Asymptotic Analysis of the MUSIC Null-Spectrum (MUSIC Null-Spectrum의 점근적 해석)

  • 윤진선;김상엽;김선용;박성일;손재철;송익호;최진호
    • Proceedings of the Korean Institute of Communication Sciences Conference
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    • 1991.10a
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    • pp.115-118
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    • 1991
  • In this paper we derived the asymptotic distribution of the MUSIC null-spectrum, from which an exact expression of the asymptotic variance of the MUSIC null-spectrum can be obtained. From this result in addition an explicit expression of the normalized standard deviation (NSD) has been derived and it is shown that the NSD is affected by the number of sensors and the number of signals.