• Title/Summary/Keyword: asymmetric distributions

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Rank Scores for Linear Models under Asymmetric Distributions

  • Choi, Young-Hun
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.359-368
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    • 2006
  • In this paper we derived the asymptotic relative efficiency, ARE(ms, rs), of our new score function with respect to the McKean and Sievers scores for the asymmetric error distributions which often occur in practice. We thoroughly explored the asymptotic relative efficiency, ARE(ms, rs), of our score function that provides much improvement over the McKean and Sievers scores for all values of r and s under asymmetric distributions.

ON THE WEAK LIMIT THEOREMS FOR GEOMETRIC SUMMATIONS OF INDEPENDENT RANDOM VARIABLES TOGETHER WITH CONVERGENCE RATES TO ASYMMETRIC LAPLACE DISTRIBUTIONS

  • Hung, Tran Loc
    • Bulletin of the Korean Mathematical Society
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    • v.58 no.6
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    • pp.1419-1443
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    • 2021
  • The asymmetric Laplace distribution arises as a limiting distribution of geometric summations of independent and identically distributed random variables with finite second moments. The main purpose of this paper is to study the weak limit theorems for geometric summations of independent (not necessarily identically distributed) random variables together with convergence rates to asymmetric Laplace distributions. Using Trotter-operator method, the orders of approximations of the distributions of geometric summations by the asymmetric Laplace distributions are established in term of the "large-𝒪" and "small-o" approximation estimates. The obtained results are extensions of some known ones.

Adaptive L-estimation for regression slope under asymmetric error distributions (비대칭 오차모형하에서의 회귀기울기에 대한 적합된 L-추정법)

  • 한상문
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.79-93
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    • 1993
  • We consider adaptive L-estimation of estimating slope parameter in regression model. The proposed estimator is simple extension of trimmed least squares estimator proposed by ruppert and carroll. The efficiency of the proposed estimator is especially well compared with usual least squares estimator, least absolute value estimator, and M-estimators designed for asymmetric distributions under asymmetric error distributions.

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Comparison of different distributions of viscous damper properties in asymmetric-plan frames

  • Landi, Luca;Molari, Andrea;Diotallevi, Pier Paolo
    • Earthquakes and Structures
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    • v.18 no.2
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    • pp.233-248
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    • 2020
  • In this article, one of the procedures to design viscous dampers proposed in literature is applied to 3D asymmetric-plan buildings, considering different distributions for the damping coefficients, which are assumed to be proportional to specific structural or response parameters. The main purpose was to investigate the effectiveness of different vertical and in-plan distributions of the damping coefficients of nonlinear viscous dampers for the seismic retrofit of existing buildings. For comparison purposes, all the distributions were applied utilizing both a simplified and an extended method for the 3D structures, where the simplified method takes into account only the translation in the seismic direction, and the extended method considers the translations along the two orthogonal directions together with the floor rotations. The proposed distributions were then applied to a typical case study involving an asymmetric-plan six-storey RC building. The effectiveness of the different distributions was examined through time-history analyses, assuming nonlinear behaviour for both the viscous dampers and the structural elements. The results of the nonlinear dynamic analyses were examined in terms of maximum and residual inter-storey drifts, peak floor accelerations and maximum damper forces.

Hidden truncation circular normal distribution

  • Kim, Sung-Su;Sengupta, Ashis
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.4
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    • pp.797-805
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    • 2012
  • Many circular distributions are known to be not only asymmetric but also bimodal. Hidden truncation method of generating asymmetric distribution is applied to a bivariate circular distribution to generate an asymmetric circular distribution. While many other existing asymmetric circular distributions can only model an asymmetric data, this new circular model has great flexibility in terms of asymmetry and bi-modality. Some properties of the new model, such as the trigonometric moment generating function, and asymptotic inference about the truncation parameter are presented. Simulation and real data examples are provided at the end to demonstrate the utility of the novel distribution.

Folded Ranked Set Sampling for Asymmetric Distributions

  • Bani-Mustafa, Ahmed;Al-Nasser, Amjad D.;Aslam, Muhammad
    • Communications for Statistical Applications and Methods
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    • v.18 no.1
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    • pp.147-153
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    • 2011
  • In this paper a new sampling procedure for estimating the population mean is introduced. The performance of the new population mean estimator is discussed, along with its properties, and it is shown that the proposed method generates an unbiased estimator. The relative efficiency of the suggested estimator is computed, in regards to the simple random sample(SRS), and comparisons are made to the ranked set sampling(RSS) and extreme ranked set sampling(ERSS) estimators used for asymmetric distributions. The results indicate that the proposed estimator is more efficient than the estimators based on the ERSS. In addition, the folded ranked set sampling(FRSS) procedure has an advantage over the RSS and ERSS in that it reduces the number of unused sampling units.

Asymptotic Normality for Threshold-Asymmetric GARCH Processes of Non-Stationary Cases

  • Park, J.A.;Hwang, S.Y.
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.477-483
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    • 2011
  • This article is concerned with a class of threshold-asymmetric GARCH models both for stationary case and for non-stationary case. We investigate large sample properties of estimators from QML(quasi-maximum likelihood) and QL(quasilikelihood) methods. Asymptotic distributions are derived and it is interesting to note for non-stationary case that both QML and QL give asymptotic normal distributions.

Exponential family of circular distributions

  • Kim, Sung-Su
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.6
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    • pp.1217-1222
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    • 2011
  • In this paper, we show that any circular density can be closely approximated by an exponential family of distributions. Therefore we propose an exponential family of distributions as a new family of circular distributions, which is absolutely suitable to model any shape of circular distributions. In this family of circular distributions, the trigonometric moments are found to be the uniformly minimum variance unbiased estimators (UMVUEs) of the parameters of distribution. Simulation result and goodness of fit test using an asymmetric real data set show usefulness of the novel circular distribution.

A Modified Definition on the Process Capability Index Cpk Based on Median

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.527-535
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    • 2011
  • This study proposes a modified definition about $C_{pk}$ based on median as the centering parameter in order to more easily control the process since the mean does not represent any quantile of the asymmetric process distribution. Then we consider an estimate and derive the asymptotic normality for the estimate of the modified $C_{pk}$. In addition, we provide an example with asymmetric distributions and discuss the estimation for the limiting variance that are followed by some concluding remarks.

Simultaneous Estimation of Parameters from Power Series Distributions under Asymmetric Loss

  • Chung, Youn-Shik;Dipak K. Dey
    • Journal of the Korean Statistical Society
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    • v.23 no.1
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    • pp.151-166
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    • 1994
  • Let $X_1, \cdot, X_p$ be p independent random variables, where each $X_i$ has a distribution belonging to one parameter discrete power series distribution. The problem is to simultaneously estimate the unknown parameters under an asymmetric loss. Several new classes of dominating estimators are obtained by solving certain difference inequality.

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