• Title/Summary/Keyword: Weighted Function

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CONVERGENCE OF WEIGHTED U-EMPIRICAL PROCESSES

  • Park, Hyo-Il;Na, Jong-Hwa
    • Journal of the Korean Statistical Society
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    • v.33 no.4
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    • pp.353-365
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    • 2004
  • In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

Better Estimators of Multiple Poisson Parameters under Weighted Loss Function

  • Kim, Jai-Young
    • Journal of the military operations research society of Korea
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    • v.11 no.2
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    • pp.69-82
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    • 1985
  • In this study, we consider the simultaneous estimation of the parameters of the distribution of p independent Poisson random variables using the weighted loss function. The relation between the estimation under the weighted loss function and the case when more than one observation is taken from some population is studied. We derive an estimator which dominates Tsui and Press's estimator when certain conditions hold. We also derive an estimator which dominates the maximum likelihood estimator(MLE) under the various loss function. The risk performances of proposed estimators are compared to that of MLE by computer simulation.

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Uniqueness of Meromorphic Functions Sharing a Small Function with Their Differential Polynomials

  • Banerjee, Abhijit
    • Kyungpook Mathematical Journal
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    • v.49 no.4
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    • pp.651-666
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    • 2009
  • With the aid of weakly weighted sharing and a recently introduced sharing notion in [3] known as relaxed weighted sharing we investigate the uniqueness of meromorphic functions sharing a small function with its differential polynomials. Our results will improve and supplement all the results obtained by Zhang and Yang [17] as well as a substantial part of the results recently obtained by the present author [2] and thus provide a better answer to the questions posed by Yu [14] in this regard.

Simulation of Whole Body Posture during Asymmetric Lifting (비대칭 들기 작업의 3차원 시뮬레이션)

  • 최경임
    • Journal of the Korea Safety Management & Science
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    • v.4 no.2
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    • pp.11-22
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    • 2002
  • In this study, an asymmetric lifting posture prediction model was developed, which was a three-dimensional model with 12 links and 23 degrees of freedom open kinematic chains. Although previous researchers have proposed biomechanical, psychophysical, or physiological measures as cost functions, for solving redundancy, they lack in accuracy in predicting actual lifting postures and most of them are confined to the two-dimensional model. To develop an asymmetric lifting posture prediction model, we used the resolved motion method for accurately simulating the lifting motion in a reasonable time. Furthermore, in solving the redundant problem of the human posture prediction, a moment weighted Joint Range Availability (JRA) was used as a cost function in order to consider dynamic lifting. However, it is known that the moment weighted JRA as a cost function predicted the lower extremity and L5/S1 joint motions better than the upper extremities, while the constant weighted JRA as a cost function predicted the latter better than the former. To compensate for this, we proposed a hybrid moment weighted JRA as a new cost function with moment weighted for only the lower extremity. In order to validate the proposed cost function, the predicted and real lifting postures for various lifting conditions were compared by using the root mean square(RMS) error. This hybrid JRA reduced RMS more than the previous cost functions. Therefore, it is concluded that the cost function of a hybrid moment weighted JRA can be used to predict three-dimensional lifting postures. To compare with the predicted trajectories and the real lifting movements, graphical validations were performed. The results also showed that the hybrid moment weighted cost function model was found to have generated the postures more similar to the real movements.

WEIGHTED COMPOSITION OPERATORS FROM BERGMAN SPACES INTO WEIGHTED BLOCH SPACES

  • LI SONGXIAO
    • Communications of the Korean Mathematical Society
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    • v.20 no.1
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    • pp.63-70
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    • 2005
  • In this paper we study bounded and compact weighted composition operator, induced by a fixed analytic function and an analytic self-map of the open unit disk, from Bergman space into weighted Bloch space. As a corollary, obtain the characterization of composition operator from Bergman space into weighted Bloch space.

CERTAIN WEIGHTED MEAN INEQUALITY

  • Kim, Namkwon
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.18 no.3
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    • pp.279-282
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    • 2014
  • In this paper, we report a new sharp inequality of interpolation type in $\mathbb{R}^n$. This inequality is for controlling weighted average of a function via $L^n$ norm of the gradient of a function together with its' certain exponential norm.

DISTRIBUTION OF VALUES OF DIFFERENCE OPERATORS CONCERNING WEAKLY WEIGHTED SHARING

  • SHAW, ABHIJIT
    • Journal of applied mathematics & informatics
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    • v.40 no.3_4
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    • pp.545-562
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    • 2022
  • Using the conception of weakly weighted sharing we discussed the value distribution of the differential product functions constructed with a polynomial and difference operator of entire function. Here we established two uniqueness result on product of difference operators when two such functions share a small function.

On Estimating the Hazard Rate for Samples from Weighted Distributions

  • Ahmad, Ibrahim A.
    • International Journal of Reliability and Applications
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    • v.1 no.2
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    • pp.133-143
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    • 2000
  • Data from weighted distributions appear, among other situations, when some of the data are missing or are damaged, a case that is important in reliability and life testing. The kernel method for hazard rate estimation is discussed for these data where the basic large sample properties are given. As a by product, the basic properties of the kernel estimate of the distribution function for data from weighted distribution are presented.

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