• Title/Summary/Keyword: Biased Data

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THE LENGTH-BIASED POWERED INVERSE RAYLEIGH DISTRIBUTION WITH APPLICATIONS

  • MUSTAFA, ABDELFATTAH;KHAN, M.I.
    • Journal of applied mathematics & informatics
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    • v.40 no.1_2
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    • pp.1-13
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    • 2022
  • This article introduces a new distribution called length-biased powered inverse Rayleigh distribution. Some of its statistical properties are derived. Maximum likelihood procedure is applied to report the point and interval estimations of all model parameters. The proposed distribution is also applied to two real data sets for illustrative purposes.

Biased SNR Estimation using Pilot and Data Symbols in BPSK and QPSK Systems

  • Park, Chee-Hyun;Hong, Kwang-Seok;Nam, Sang-Won;Chang, Joon-Hyuk
    • Journal of Communications and Networks
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    • v.16 no.6
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    • pp.583-591
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    • 2014
  • In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

Expressions for Shrinkage Factors of PLS Estimator

  • Kim, Jong-Duk
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.4
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    • pp.1169-1180
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    • 2006
  • Partial least squares regression (PLS) is a biased, non-least squares regression method and is an alternative to the ordinary least squares regression (OLS) when predictors are highly collinear or predictors outnumber observations. One way to understand the properties of biased regression methods is to know how the estimators shrink the OLS estimator. In this paper, we introduce an expression for the shrinkage factor of PLS and develop a new shrinkage expression, and then prove the equivalence of the two representations. We use two near-infrared (NIR) data sets to show general behavior of the shrinkage and in particular for what eigendirections PLS expands the OLS coefficients.

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Preservation of some partial orderings of life distributions under length biased distributions (기간편의분포하(其間偏倚分布下)에서 수명분포(壽命分布)의 편순서(偏順序) 보존(保存))

  • Choi, Jeen-Kap;Kim, Sang-Lyong
    • Journal of the Korean Data and Information Science Society
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    • v.4
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    • pp.45-51
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    • 1993
  • For studies in reliability, biometry and survival analysis, the length biased distribution is frequently appropriate for certain natural sampling plans. So, we shall convey the preservation of some partial orderings under life length biasd distributions and closures of ILR and NBU classes under life length biasd distributions.

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Estimation of Income Distribution for Domestic Grape-producing Farms Based on the Subjective Simulation Process (주관적 모의실험을 기반으로 한 국내 포도농가의 소득 분포 추정)

  • Koo, Seung-Mo
    • Korean Journal of Agricultural Science
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    • v.37 no.2
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    • pp.315-321
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    • 2010
  • Decision-makings or the related policies regarding domestic grape production heavily depends upon the known market price data and official statistics periodically announced by government, at national level. However, usual adaption of the 'simple means' from these data may bring seriously biased decision-makings when the original data are biased, especially when the data are not convinced to be normal distributions to decision makers. In this regards, this study employs Monte Carlo simulation technique to overcome the limitations, based on the decision makers' subjective assumptions on the known data, and, tries to come up with flexible range of business information regarding grape-producing farm income. The approach used in this study also provides possibility that it may be useful when adapting subjective assumptions from various statistical distributions.

Permanent Magnet Biased Linear Magnetic Bearing for High-Precision Maglev Stage (초정밀 자기부상 스테이지의 위치제어를 위한 영구자석형 선형 자기베어링의 개발)

  • Lee, Sang-Ho;Chang, Jee-Uk;Kim, Oui-Serg;Han, Dong-Chul
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.164-169
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    • 2001
  • The active magnetic bearing has many advantages - an active positioning, no contact and lubrication free motion - and is widely used in high precision motion stages. But, the conventional magnetic bearings composed of electromagnets only are power consuming due to their bias current and have the excessive heat generation, which can make the repeatability of the positioning system worse. To overcome this drawback, we developed a novel permanent magnet (PM) biased linear magnetic bearing for a high precision magnetically levitated stage. The permanent magnets provide a bias flux and generate a bias force, and the electromagnet increases or reduces a flux of the permanent magnets and gives a levitation force. This paper presents a theoretical magnetic circuit analysis, FEM analysis and experimental data from the 1-DOF tests, and compares the theoretical power consumption of the electromagnetic bearings and the PM biased linear magnetic bearings. The PM biased linear magnetic bearing presented in this paper gives better load capacity but lower power consumption than a conventional electromagnetic bearing and will be adopted in our 6-DOF high precision linear positioning maglev stage.

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Molecular Markers in Sex Differences in Cancer

  • Shin, Ji Yoon;Jung, Hee Jin;Moon, Aree
    • Toxicological Research
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    • v.35 no.4
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    • pp.331-341
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    • 2019
  • Cancer is one of the common causes of death with a high degree of mortality, worldwide. In many types of cancers, if not all, sex-biased disparities have been observed. In these cancers, an individual's sex has been shown to be one of the crucial factors underlying the incidence and mortality of cancer. Accumulating evidence suggests that differentially expressed genes and proteins may contribute to sex-biased differences in male and female cancers. Therefore, identification of these molecular differences is important for early diagnosis of cancer, prediction of cancer prognosis, and determination of response to specific therapies. In the present review, we summarize the differentially expressed genes and proteins in several cancers including bladder, colorectal, liver, lung, and nonsmall cell lung cancers as well as renal clear cell carcinoma, and head and neck squamous cell carcinoma. The sex-biased molecular differences were identified via proteomics, genomics, and big data analysis. The identified molecules represent potential candidates as sex-specific cancer biomarkers. Our study provides molecular insights into the impact of sex on cancers, suggesting strategies for sex-biased therapy against certain types of cancers.

A review of analysis methods for secondary outcomes in case-control studies

  • Schifano, Elizabeth D.
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.103-129
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    • 2019
  • The main goal of a case-control study is to learn the association between various risk factors and a primary outcome (e.g., disease status). Particularly recently, it is also quite common to perform secondary analyses of the case-control data in order to understand certain associations between the risk factors of the primary outcome. It has been repeatedly documented with case-control data, association studies of the risk factors that ignore the case-control sampling scheme can produce highly biased estimates of the population effects. In this article, we review the issues of the naive secondary analyses that do not account for the biased sampling scheme, and also the various methods that have been proposed to account for the case-control ascertainment. We additionally compare the results of many of the discussed methods in an example examining the association of a particular genetic variant with smoking behavior, where the data were obtained from a lung cancer case-control study.

A Decision Model with Expert's Biased Information Transmission

  • Kimk, Kwang-Jae;Jeong, Byong-Ho;Kim, Soung-Hie
    • Journal of the Korean Operations Research and Management Science Society
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    • v.13 no.2
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    • pp.1-8
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    • 1988
  • This study suggests on optimal process when decision maker is confronted with expert's biased information under the situation that the bias is caused mainly by the difference of their interest. In order to make honest transmission of expert's probabilistic information, the concept of expert use and scoring rule to provide expert with an incentive is used in this paper. And expected regret concept is introduced to evaluate the value of expert's information. A simple example is also shown.

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Note on Stochastic Orders through Length Biased Distributions

  • Choi, Jeen-Kap;Lee, Jin-Woo
    • Journal of the Korean Data and Information Science Society
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    • v.10 no.1
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    • pp.243-250
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    • 1999
  • We consider $Y=X{\lambda}Z,\;{\lambda}>0$, where X and Z are independent random variables, and Y is the length biased distribution or the equilibrium distribution of X. The purpose of this paper is to consider the distribution of X or Y when the distribution of Z is given and the distribution of Z when the distribution of X or Y is given, In particular, we obtain that the necessary and sufficient conditions for X to be $X^{2}({\upsilon})\;is\;Z{\sim}X^{2}(2)\;and\;for\;Z\;to\;be\;X^{2}(1)\;is\;X{\sim}IG({\mu},\;{\mu}^{2}/{\lambda})$, where $IG({\mu},\;{\mu}^{2}/{\lambda})$ is two-parameter inverse Gaussian distribution. Also we show that X is smaller than Y in the reverse Laplace transform ratio order if and only if $X_{e}$ is smaller than $Y_{e}$ in the Laplace transform ratio order. Finally, we can get the results that if X is smaller than Y in the Laplace transform ratio order, then $Y_{L}$ is smaller than $X_{L}$ in the Laplace transform order, and that if X is smaller than Y in the reverse Laplace transform ratio order, then $_{\mu}X_{L}$ is smaller than $_{\nu}Y_{L}$ in the Laplace transform order.

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