• Title/Summary/Keyword: asymptotic consistency

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Micro-Mechanical Approach for Spanwise Periodically and Heterogeneously Beam-like Structures

  • Lee, Chang-Yong
    • Journal of the Korean Solar Energy Society
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    • v.36 no.3
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    • pp.9-16
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    • 2016
  • This paper discusses a refined model for investigating the micro-mechanical behavior of beam-like structures, which are composed of various elastic moduli and complex geometries varying through the cross-section directions and are also periodically-repeated and heterogeneous along the axial direction. Following the previous work (Lee and Yu, 2011), the original three-dimensional static problem is first formulated in a unified and compact form using the concept of decomposition of the rotation tensor. Taking advantage of the smallness of the cross-sectional dimension-to-length parameter and the micro-to-macro heterogeneity, while also performing homogenization along the dimensional reduction simultaneously, the variational asymptotic method is rigorously used to construct a total energy function, which is asymptotically correct up to the second order. Furthermore, through the transformation procedure based on the pure kinematic relations and the linearized equilibrium equations, a generalized Timoshenko model is systematically established. For the purpose of dealing with realistic and complex geometries and constituent materials at the microscopic level, this present approach is incorporated into a commercial analysis package. A few examples available in literature are used to demonstrate the consistency and efficiency of this proposed model, especially for the structures, in which the effects of transverse shear deformations are significant.

Revisiting the Bradley-Terry model and its application to information retrieval

  • Jeon, Jong-June;Kim, Yongdai
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.5
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    • pp.1089-1099
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    • 2013
  • The Bradley-Terry model is widely used for analysis of pairwise preference data. We explain that the popularity of Bradley-Terry model is gained due to not only easy computation but also some nice asymptotic properties when the model is misspecified. For information retrieval required to analyze big ranking data, we propose to use a pseudo likelihood based on the Bradley-Terry model even when the true model is different from the Bradley-Terry model. We justify using the Bradley-Terry model by proving that the estimated ranking based on the proposed pseudo likelihood is consistent when the true model belongs to the class of Thurstone models, which is much bigger than the Bradley-Terry model.

Estimation of continuous odds ratio function with censored data (중도절단된 자료를 포함한 승산비 연속함수의 추정)

  • Kim, Jung-Suk;Kwon, Chang-Hee
    • 한국디지털정책학회:학술대회논문집
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    • 2006.12a
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    • pp.327-336
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    • 2006
  • The odds ratio is used for assessing the disease-exposure association, because epidemiological data for case-control of cohort studies are often summarized into 2 ${\times}$ 2 tables. In this paper we define the odds ratio function(ORF) that extends odds ratio used on discrete survival event data to continuous survival time data and propose estimation procedures with censored data. The first one is a nonparametric estimator based on the Nelson-Aalen estimator of comulative hazard function, and the others are obtained using the concept of empirical odds ratio. Asymptotic properties such as consistency and weak convergence results are also provided. The ORF provides a simple interpretation and is comparable to survival function or comulative hazard function in comparing two groups. The mean square errors are investigated via Monte Carlo simulation. The result are finally illustrated using the Melanoma data.

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Bootstrap confidence interval for survival function in the Koziol-Green model (KOZIOL-GREEN 모형에서 생존함수에 대한 붓스트랩 구간추정)

  • 조길호;정성화;최달우;최현숙
    • The Korean Journal of Applied Statistics
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    • v.11 no.1
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    • pp.151-161
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    • 1998
  • We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.

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Asymptotic Properties of Variance Change-point in the Long-memory Process

  • Chu Minjeong;Cho Sinsup
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.23-26
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    • 2000
  • It is noted that many econometric time series have long-memory properties. A long-memory process, or strongly dependent process, is characterized by hyperbolic decaying autocorrelations and unbounded spectral density at the origin. Since the long-memory property can be observed by data obtained from rather a long period, there is some possibility of parameter change in the process. In this paper, we consider the estimation of change-point when there is a change in the variance of a long-memory process. The estimator is based on some reasonable statistic and the consistency is shown using Taqqu's strong reduction theorem

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A Comparison of Size and Power of Tests of Hypotheses on Parameters Based on Two Generalized Lindley Distributions

  • Okwuokenye, Macaulay;Peace, Karl E.
    • Communications for Statistical Applications and Methods
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    • v.22 no.3
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    • pp.233-239
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    • 2015
  • This study compares two generalized Lindley distributions and assesses consistency between theoretical and analytical results. Data (complete and censored) assumed to follow the Lindley distribution are generated and analyzed using two generalized Lindley distributions, and maximum likelihood estimates of parameters from the generalized distributions are obtained. Size and power of tests of hypotheses on the parameters are assessed drawing on asymptotic properties of the maximum likelihood estimates. Results suggest that whereas size of some of the tests of hypotheses based on the considered generalized distributions are essentially ${\alpha}$-level, some are possibly not; power of tests of hypotheses on the Lindley distribution parameter from the two distributions differs.

UNIFORM ASYMPTOTICS IN THE EMPIRICAL MEAN RESIDUAL LIFE PROCESS

  • Bae, Jong-Sic;Kim, Sung-Yeun
    • Journal of the Korean Mathematical Society
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    • v.43 no.2
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    • pp.225-239
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    • 2006
  • In [5], Csorgo and Zitikis exposed the strong $uniform-over-[0,\;{\infty}]$ consistency, and weak $uniform-over-[0,\;{\infty}]$ approximation of the empirical mean residual life process by employing weight functions. We carry on the uniform asymptotic behaviors of the empirical mean residual life process over the whole positive half line by representing the process as an integral form. We compare our results with those of Yang [15], Hall and Wellner [8], and Csorgo and Zitikis [5].

Better Statistical Test for Process Capability Index $C_p$ (공정능력지수 $C_p$에 대한 효율적인 가설검정)

  • Cho, Joong-Jae;Lim, Soo-Duck
    • Journal of Korean Society for Quality Management
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    • v.34 no.3
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    • pp.66-72
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    • 2006
  • The process capability indices are widely used to measure the capability of the process to manufacture items within the specified tolerance. Most evaluations on process capability indices focus on point estimates, which may result in unreliable assessments of process performance. The index $C_p$ has been widely used in various industries to assess process performance. In this paper, we propose new testing procedure on assessing $C_p$ index for practitioners to use in determining whether a given process is capable. The provided approach is easy to use and the decision making is more reliable. Whether a process is clearly normal or nonnormal, our bootstrap testing procedure could be applied effectively without the complexity of calculation. A numerical result based on the proposed approach is illustrated.

Partially linear multivariate regression in the presence of measurement error

  • Yalaz, Secil;Tez, Mujgan
    • Communications for Statistical Applications and Methods
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    • v.27 no.5
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    • pp.511-521
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    • 2020
  • In this paper, a partially linear multivariate model with error in the explanatory variable of the nonparametric part, and an m dimensional response variable is considered. Using the uniform consistency results found for the estimator of the nonparametric part, we derive an estimator of the parametric part. The dependence of the convergence rates on the errors distributions is examined and demonstrated that proposed estimator is asymptotically normal. In main results, both ordinary and super smooth error distributions are considered. Moreover, the derived estimators are applied to the economic behaviors of consumers. Our method handles contaminated data is founded more effectively than the semiparametric method ignores measurement errors.

Kernel Estimation of Hazard Ratio Based on Censored Data

  • Choi, Myong-Hui;Lee, In-Suk;Song, Jae-Kee
    • Journal of the Korean Data and Information Science Society
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    • v.12 no.2
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    • pp.125-143
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    • 2001
  • We, in this paper, propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation. Two examples are illustrated for our results.

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