• Title/Summary/Keyword: asymptotic density

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The Asymptotic Unbiasedness of $S^2$ in the Linear Regression Model with Dependent Errors

  • Lee, Sang-Yeol;Kim, Young-Won
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.235-241
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    • 1996
  • The ordinary least squares estimator of the disturbance variance in the linear regression model with stationary errors is shown to be asymptotically unbiased when the error process has a spectral density bounded from the above and away from zero. Such error processes cover a broad class of stationary processes, including ARMA processes.

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Simultaneous Confidence Regions for Spatial Autoregressive Spectral Densities

  • Ha, Eun-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.2
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    • pp.397-404
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    • 1999
  • For two-dimensional causal spatial autoregressive processes, we propose and illustrate a method for determining asymptotic simultaneous confidence regions using Yule-Walker, unbiased Yule-Walker and least squres estimators. The spectral density for first-order spatial autoregressive model are looked at in more detail. Finite sample properties based on simulation study we also presented.

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On the Selection of Bezier Points in Bezier Curve Smoothing

  • Kim, Choongrak;Park, Jin-Hee
    • The Korean Journal of Applied Statistics
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    • v.25 no.6
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    • pp.1049-1058
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    • 2012
  • Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

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.

Construction of Optimal Concatenated Zigzag Codes Using Density Evolution with a Gaussian Approximation

  • Hong Song-Nam;Shin Dong-Joon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.9C
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    • pp.825-830
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    • 2006
  • Capacity-approaching codes using iterative decoding have been the main subject of research activities during past decade. Especially, LDPC codes show the best asymptotic performance and density evolution has been used as a powerful technique to analyze and design good LDPC codes. In this paper, we apply density evolution with a Gaussian approximation to the concatenated zigzag (CZZ) codes by considering both flooding and two-way schedulings. Based on this density evolution analysis, the threshold values are computed for various CZZ codes and the optimal structure of CZZ codes for various code rates are obtained. Also, simulation results are provided to conform the analytical results.

Minimum Hellinger Distance Estimation and Minimum Density Power Divergence Estimation in Estimating Mixture Proportions

  • Pak, Ro-Jin
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1159-1165
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    • 2005
  • Basu et al. (1998) proposed a new density-based estimator, called the minimum density power divergence estimator (MDPDE), which avoid the use of nonparametric density estimation and associated complication such as bandwidth selection. Woodward et al. (1995) examined the minimum Hellinger distance estimator (MHDE), proposed by Beran (1977), in the case of estimation of the mixture proportion in the mixture of two normals. In this article, we introduce the MDPDE for a mixture proportion, and show that both the MDPDE and the MHDE have the same asymptotic distribution at a model. Simulation study identifies some cases where the MHDE is consistently better than the MDPDE in terms of bias.

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The Minimum Squared Distance Estimator and the Minimum Density Power Divergence Estimator

  • Pak, Ro-Jin
    • Communications for Statistical Applications and Methods
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    • v.16 no.6
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    • pp.989-995
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    • 2009
  • Basu et al. (1998) proposed the minimum divergence estimating method which is free from using the painful kernel density estimator. Their proposed class of density power divergences is indexed by a single parameter $\alpha$ which controls the trade-off between robustness and efficiency. In this article, (1) we introduce a new large class the minimum squared distance which includes from the minimum Hellinger distance to the minimum $L_2$ distance. We also show that under certain conditions both the minimum density power divergence estimator(MDPDE) and the minimum squared distance estimator(MSDE) are asymptotically equivalent and (2) in finite samples the MDPDE performs better than the MSDE in general but there are some cases where the MSDE performs better than the MDPDE when estimating a location parameter or a proportion of mixed distributions.

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.

Validation of the Turbulent Burning Velocity Based on Asymptotic Zone Conditional Transport in Turbulent Premixed Combustion (영역조건평균에 기초한 난류예혼합 화염 전파 속도식 유도 및 검증)

  • Lee, Dong-Kyu;Huh, Kang-Y.
    • Journal of the Korean Society of Combustion
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    • v.13 no.1
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    • pp.23-30
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    • 2008
  • An analytical expression for the turbulent burning velocity is derived from the asymptotic zone conditional transport equation at the leading edge. It is given as a sum of laminar and turbulent contributions, the latter of which is given as a product of turbulent diffusivity in unburned gas and inverse scale of wrinkling at the leading edge. It was previously shown that the inverse scale is equal to four times the maximum flame surface density in the wrinkled flamelet regime [1]. The linear behavior between $U_T$ and u' shows deviation with the inverse scale decreasing due to the effect of a finite flamelet thickness at higher turbulent intensities. DNS results show that $U_T/S^0_{Lu}$ may be given as a function of two dimensionless parameters, $u'/S^0_{Lu}$ and $l_t/\delta_F$, which may be transformed into another relationship in terms of $u'/S^0_{Lu}$, and Ka. A larger $l_t/{\delta}_F$ or a smaller Ka leads to a smaller scale of wrinkling, hence a larger turbulent burning velocity in the limited range of $u'/S^0_{Lu}$. Good agreement is achieved between the analytical expression and the turbulent burning velocities from DNS in both wrinkled and thickened-wrinkled flame regimes.

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MODEL DUST ENVELOPES FOR ASYMPTOTIC GIANT BRANCH STARS. II. CARBON STARS

  • Suh, Kyung-Won;Kwoun, Hee-Joung
    • Journal of Astronomy and Space Sciences
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    • v.12 no.2
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    • pp.168-178
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    • 1995
  • We have modeled the dust envelopes around carbon stars with close attention to the evolution of the structure of the dust shells. We use various dust density distributions to take account the effect of the superwind due to the helium shell flash by adding a density increased region. Depending on the position and quality of the density increased region, the model results are different from the results with conventional density distribution. The new results fit the observations of some carbon stars better. The IR two-color diagrams comparing the results of the super wind models and IRAS observation of 252 carbon stars have been made. The new results can explain much wider regions on the IR two-color diagrams.

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