Relevant bibliographies by topics / Best linear unbiased estimator (BLUE)

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Best linear unbiased estimator (BLUE)'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Best linear unbiased estimator (BLUE)"

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Wu, Jong-Wuu, Sheau-Chiann Chen, Wen-Chuan Lee, and Heng-Yi Lai. "Weighted Moments Estimators of the Parameters for the Extreme Value Distribution Based on the Multiply Type II Censored Sample." Scientific World Journal 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/281624.

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We propose the weighted moments estimators (WMEs) of the location and scale parameters for the extreme value distribution based on the multiply type II censored sample. Simulated mean squared errors (MSEs) of best linear unbiased estimator (BLUE) and exact MSEs of WMEs are compared to study the behavior of different estimation methods. The results show the best estimator among the WMEs and BLUE under different combinations of censoring schemes.
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Hansen, Bruce E. "A Modern Gauss–Markov Theorem." Econometrica 90, no. 3 (2022): 1283–94. http://dx.doi.org/10.3982/ecta19255.

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This paper presents finite‐sample efficiency bounds for the core econometric problem of estimation of linear regression coefficients. We show that the classical Gauss–Markov theorem can be restated omitting the unnatural restriction to linear estimators, without adding any extra conditions. Our results are lower bounds on the variances of unbiased estimators. These lower bounds correspond to the variances of the the least squares estimator and the generalized least squares estimator, depending on the assumption on the error covariances. These results show that we can drop the label “linear est
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Isotalo, Jarkko, Märt Möls, and Simo Puntanen. "Invariance of the BLUE under the linear fixed and mixed effects models." Acta et Commentationes Universitatis Tartuensis de Mathematica 10 (December 31, 2006): 69–76. http://dx.doi.org/10.12697/acutm.2006.10.06.

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We consider the estimation of the parametric function X1β1 under the partitioned linear fixed effects model y=X1β1+X2β2+ε and the linear mixed effects model y=X1β1+X2γ2+ε, where γ2 is considered to be a random vector. Particularly, we consider when the best linear unbiased estimator, BLUE, of X1β1 under the linear fixed effects model equals the corresponding BLUE under the linear mixed effects model.
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IDOWU, Janet Iyabo, Olasunkanmi James OLADAPO, Abiola Timothy OWOLABİ, Kayode AYİNDE, and Oyinlade AKİNMOJU. "Combating Multicollinearity: A New Two-Parameter Approach." Nicel Bilimler Dergisi 5, no. 1 (2023): 1–31. http://dx.doi.org/10.51541/nicel.1084768.

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The ordinary least square (OLS) estimator is the Best Linear Unbiased Estimator (BLUE) when all linear regression model assumptions are valid. The OLS estimator, however, becomes inefficient in the presence of multicollinearity. To circumvent the problem of multicollinearity, various one and two-parameter estimators have been proposed. This paper a new two-parameter estimator called Liu-Kibria Lukman Estimator (LKL) estimator. The theoretical and simulation results show that the proposed estimator performs better than some existing estimators considered in this study under some conditions, usi
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Fransiska, Welly, Sigit Nugroho, and Ramya Rachmawati. "A Comparison of Weighted Least Square and Quantile Regression for Solving Heteroscedasticity in Simple Linear Regression." Journal of Statistics and Data Science 1, no. 1 (2022): 19–29. http://dx.doi.org/10.33369/jsds.v1i1.21011.

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Regression analysis is the study of the relationship between dependent variable and one or more independent variables. One of the important assumption that must be fulfilled to get the regression coefficient estimator Best Linear Unbiased Estimator (BLUE) is homoscedasticity. If the homoscedasticity assumption is violated then it is called heteroscedasticity. The consequences of heteroscedasticity are the estimator remain linear and unbiased, but it can cause estimator haven‘t a minimum variance so the estimator is no longer BLUE. The purpose of this study is to analyze and resolve the violati
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Shen, Bing-liang, Shuo Wang, Wang-xue Chen, and Meng Chen. "Fisher information for generalized Rayleigh distribution in ranked set sampling design with application to parameter estimation." Applied Mathematics-A Journal of Chinese Universities 37, no. 4 (2022): 615–30. http://dx.doi.org/10.1007/s11766-022-4450-5.

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AbstractIn the current paper, we considered the Fisher information matrix from the generalized Rayleigh distribution (GR) distribution in ranked set sampling (RSS). The numerical results show that the ranked set sample carries more information about λ and α than a simple random sample of equivalent size. In order to give more insight into the performance of RSS with respect to (w.r.t.) simple random sampling (SRS), a modified unbiased estimator and a modified best linear unbiased estimator (BLUE) of scale and shape λ and α from GR distribution in SRS and RSS are studied. The numerical results
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Hoque, Md Ariful, Zoran Bursac, and B. M. Golam Kibria. "Inferences About Two-Parameter Multicollinear Gaussian Linear Regression Models: An Empirical Type I Error and Power Comparison." Stats 8, no. 2 (2025): 28. https://doi.org/10.3390/stats8020028.

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In linear regression analysis, the independence assumption is crucial and the ordinary least square (OLS) estimator generally regarded as the Best Linear Unbiased Estimator (BLUE) is applied. However, multicollinearity can complicate the estimation of the effect of individual variables, leading to potential inaccurate statistical inferences. Because of this issue, different types of two-parameter estimators have been explored. This paper compares t-tests for assessing the significance of regression coefficients, including several two-parameter estimators. We conduct a Monte Carlo study to eval
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Babayan, Nikolay, and Mamikon S. Ginovyan. "On exponential decay of the variance of BLUE for the mean of a stationary sequence." Studia Scientiarum Mathematicarum Hungarica 56, no. 4 (2019): 482–91. http://dx.doi.org/10.1556/012.2019.56.4.1448.

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Abstract In this paper, we obtain necessary as well as sufficient conditions for exponential rate of decrease of the variance of the best linear unbiased estimator (BLUE) for the unknown mean of a stationary sequence possessing a spectral density. In particular, we show that a necessary condition for variance of BLUE to decrease to zero exponentially is that the spectral density vanishes on a set of positive Lebesgue measure in any vicinity of zero.
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Attwa, Rasha Abd El-Wahab, and Taha Radwan. "Different Methods for Estimating Default Parameters of Alpha Power-Transformed Power Distributions Using Record-Breaking Data." Symmetry 16, no. 1 (2023): 30. http://dx.doi.org/10.3390/sym16010030.

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The current study addresses the estimation of the default parameters of alpha power-transformed power (APTPO) distributions. For the location and scale parameters of the APTPO distributions, we provide coefficients for both the best linear unbiased estimators (BLUE) and the best linear invariant estimators (BLIE) methods. Furthermore, we establish a forecast for future records. The parameters of the APTPO distribution are estimated using the maximum likelihood estimation method (MLE). The goodness-of-fit test (using Akaike information criterion (AIC)) is computed using both the inter-record ti
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Yoon, Jin Hee, and Przemyslaw Grzegorzewski. "On Optimal and Asymptotic Properties of a Fuzzy L2 Estimator." Mathematics 8, no. 11 (2020): 1956. http://dx.doi.org/10.3390/math8111956.

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A fuzzy least squares estimator in the multiple with fuzzy-input–fuzzy-output linear regression model is considered. The paper provides a formula for the L2 estimator of the fuzzy regression model. This paper proposes several operations for fuzzy numbers and fuzzy matrices with fuzzy components and discussed some algebraic properties that are needed to use for proving theorems. Using the proposed operations, the formula for the variance, provided and this paper, proves that the estimators have several important optimal properties and asymptotic properties: they are Best Linear Unbiased Estimat
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Dissertations / Theses on the topic "Best linear unbiased estimator (BLUE)"

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Zhang, Keshu. "Best linear unbiased estimation fusion with constraints." ScholarWorks@UNO, 2003. http://louisdl.louislibraries.org/u?/NOD,86.

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Thesis (Ph. D.)--University of New Orleans, 2003.<br>Title from electronic submission form. "A dissertation ... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Electrical Engineering"--Dissertation t.p. Vita. Includes bibliographical references.
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Haq, Abdul. "Improvements in ranked set sampling." Thesis, University of Canterbury. Mathematics and Statistics, 2014. http://hdl.handle.net/10092/9661.

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The main focus of many agricultural, ecological and environmental studies is to develop well designed, cost-effective and efficient sampling designs. Ranked set sampling (RSS) is one of those sampling methods that can help accomplish such objectives by incorporating prior information and expert knowledge to the design. In this thesis, new RSS schemes are suggested for efficiently estimating the population mean. These sampling schemes can be used as cost-effective alternatives to the traditional simple random sampling (SRS) and RSS schemes. It is shown that the mean estimators under the propose
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Mbah, Alfred Kubong. "On the theory of records and applications." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002216.

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Krishnan, Rajet. "Problems in distributed signal processing in wireless sensor networks." Thesis, Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1351.

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Teixeira, Marcos Vinícius. "Estudos sobre a implementação online de uma técnica de estimação de energia no calorímetro hadrônico do atlas em cenários de alta luminosidade." Universidade Federal de Juiz de Fora (UFJF), 2015. https://repositorio.ufjf.br/jspui/handle/ufjf/4169.

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Hsu, Chun-Chieh, and 徐俊傑. "Best linear unbiased estimator approach for RSS localization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/31932040315158613516.

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碩士<br>嶺東科技大學<br>資訊管理與應用研究所<br>100<br>The Global Positioning System (GPS) is a successful and best satellite navigation system that provides mobile location in all environments of outdoor. But it cannot keep the best line of sight, and the accuracy of location will be degraded in the environment of poor satellite signal. Thus, the wireless sensor network is a popular research project in recent years. The location technologies include received signal strength (RSS), time of arrival (TOA), time difference of arrival (TDOA), and angle of arrival (AOA). However, the non-line of sight and the multip
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Zhang, Ruitao. "Developing best linear unbiased estimator in finite population accounting for measurement error due to interviewer." 2010. https://scholarworks.umass.edu/dissertations/AAI3427614.

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Godambe (1955) give a general finite population sampling model and proved that a best linear unbiased estimator (BLUE) of population total does not exist when there is no measurement error. In this research, Godambe’s linear estimator is expanded to include two types of measurement errors and their mixture. We check Godambe’s non-existence theorem and explore the method to develop the best linear unbiased estimator of the latent population total by using individual unbiased constraints and average unbiased constraints, respectively. We start from Godambe’s general framework and then reduce to
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(13991187), Joseph W. Daley. "Mixed model methods for quantitative trait loci estimation in crosses between outbred lines." Thesis, 2003. https://figshare.com/articles/thesis/Mixed_model_methods_for_quantitative_trait_loci_estimation_in_crosses_between_outbred_lines/21376767.

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<p>Methodology is developed for Quantitative Trait Loci (QTL) analysis in F<sub>2</sub> and backcross designed experiments between outbred lines using a mixed model framework through the modification of segment mapping techniques. Alleles are modelled in the F<sub>1</sub> and parental generations allowing the estimation of individual additive allele effects while accounting for QTL segregation within lines as well as differences in mean QTL effects between lines.</p> <p>Initially the theory, called F<sub>1</sub> origin mapping, is developed for a single trait scenario involving possible multip
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Book chapters on the topic "Best linear unbiased estimator (BLUE)"

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Montesinos López, Osval Antonio, Abelardo Montesinos López, and Jose Crossa. "Preprocessing Tools for Data Preparation." In Multivariate Statistical Machine Learning Methods for Genomic Prediction. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89010-0_2.

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AbstractThis data preparation chapter is of paramount importance for implementing statistical machine learning methods for genomic selection. We present the basic linear mixed model that gives rise to BLUE and BLUP and explain how to decide when to use fixed or random effects that give rise to best linear unbiased estimates (BLUE or BLUEs) and best linear unbiased predictors (BLUP or BLUPs). The R codes for fitting linear mixed model for the data are given in small examples. We emphasize tools for computing BLUEs and BLUPs for many linear combinations of interest in genomic-enabled prediction
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Mehta, Vishal. "An Improved Estimation of Parameter of Morgenstern-Type Bivariate Exponential Distribution Using Ranked Set Sampling." In Ranked Set Sampling Models and Methods. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-7556-7.ch001.

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In this chapter, the authors suggest some improved versions of estimators of Morgenstern type bivariate exponential distribution (MTBED) based on the observations made on the units of ranked set sampling (RSS) regarding the study variable Y, which is correlated with the auxiliary variable X, where (X,Y) follows a MTBED. In this chapter, they firstly suggested minimum mean squared error estimator for estimation of 𝜃2 based on censored ranked set sample and their special case; further, they have suggested minimum mean squared error estimator for best linear unbiased estimator of 𝜃2 based on cens
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Nascimento, Maxwel Rodrigues, Rogério Figueiredo Daher, Ana Kesia Faria Vidal, et al. "PARÂMETROS GENÉTICOS E PREDIÇÃO DE VALORES GENOTÍPICOS DE LINHAGENS DE ARROZ IRRIGADO EM CAMPOS DOS GOYTACAZES." In Biotecnologia de Plantas. Editora Science, 2022. https://doi.org/10.56001/22.9786500495669.10.

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O arroz é um cereal de suma importância por ser fonte de carboidratos, proteínas, vitaminas e minerais para mais da metade da população mundial. Devido a sua importância, o arroz é cultivado anualmente em cerca de 168 milhões de hectares em todo o mundo, sendo que a maior parte da produção advém do continente asiático. O objetivo desse trabalho foi estimar os parâmetros genéticos e predizer os valores genotípicos envolvidos em caracteres agronômicos de genótipos de arroz cultivados em condição de várzea, a fim de identificar as linhagens de melhor desempenho. Foram avaliados 20 genótipos de ar
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Nascimento, Maxwel Rodrigues, Rogério Figueiredo Daher, Josefa Grasiela Silva Santana, et al. "PERFORMANCE GENOTÍPICA DE LINHAGENS DE ARROZ IRRIGADO EM CAMPOS DOS GOYTACAZES VIA MODELOS MISTOS." In Biotecnologia de Plantas. Editora Science, 2022. https://doi.org/10.56001/22.9786500495669.11.

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O arroz é considerado um alimento base na dieta alimentar de mais da metade da população mundial. Seu cultivo ocorre anualmente em cerca de 168 milhões de hectares em todo o mundo, sendo que a maior parte está situada no continente asiático. Atualmente, o Brasil é o décimo primeiro maior produtor de arroz do mundo, destacando-se como o maior fora do continente asiático. O objetivo desse trabalho foi estimar os parâmetros genéticos e predizer os valores genotípicos envolvidos em caracteres agronômicos de genótipos de arroz cultivados em condição de várzea, a fim de identificar as linhagens de m
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Pawlowsky-Glahn, Vera, and Richardo A. Olea. "Cokriging." In Geostatistical Analysis of Compositional Data. Oxford University Press, 2004. http://dx.doi.org/10.1093/oso/9780195171662.003.0011.

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The problem of estimation of a coregionalization of size q using cokriging will be discussed in this chapter. Cokriging—a multivariate extension of kriging—is the usual procedure applied to multivariate regionalized problems within the framework of geostatistics. Its fundament is a distribution-free, linear, unbiased estimator with minimum estimation variance, although the absence of constraints on the estimator is an implicit assumption that the multidimensional real space is the sample space of the variables under consideration. If a multivariate normal distribution can be assumed for the ve
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Brown, Philip J. "Regularized multiple regression." In Measurement, Regression, and Calibration. Oxford University PressOxford, 1994. http://dx.doi.org/10.1093/oso/9780198522454.003.0004.

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Abstract The Gauss-Markov theorem lends considerable weight to the use of least-squares as a method of fitting a linear parametric model. It provides ‘best’ estimators. It does, however, have a very restricted notion of what is best. Firstly it confines attention to estimators linear in the response Y. Secondly it looks only at unbiased estimators. Thirdly it minimizes mean-squared error, that is, it is concerned with expected squared error or quadratic loss: in the scalar case it uses is as an estimator of θ. Even retaining quadratic loss, there may be estimators which are either biased or no
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Conference papers on the topic "Best linear unbiased estimator (BLUE)"

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Huang, Cheng, Jiayao Li, and Hao Liu. "A Closed-Form Phase Difference Estimation Method for BLE Direction Finding using the Best Linear Unbiased Estimator." In 2023 IEEE 23rd International Conference on Communication Technology (ICCT). IEEE, 2023. http://dx.doi.org/10.1109/icct59356.2023.10419676.

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Comuniello, Antonella, Alessio De Angelis, and Antonio Moschitta. "Ultrasound TDoA positioning using the Best Linear Unbiased Estimator." In 2019 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2019. http://dx.doi.org/10.1109/i2mtc.2019.8827071.

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Dikici, Engin, Fredrik Orderud, and Hans Torp. "Best linear unbiased estimator for Kalman filter based left ventricle tracking in 3D+T echocardiography." In 2012 IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA). IEEE, 2012. http://dx.doi.org/10.1109/mmbia.2012.6164741.

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Otchere, Daniel Asante, David Hodgetts, Tarek Arbi Omar Ganat, Najeeb Ullah, and Alidu Rashid. "Static Reservoir Modeling Comparing Inverse Distance Weighting to Kriging Interpolation Algorithm in Volumetric Estimation. Case Study: Gullfaks Field." In Offshore Technology Conference. OTC, 2021. http://dx.doi.org/10.4043/30919-ms.

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Abstract Understanding and characterizing the behaviour of the subsurface by combining it with a suitable statistical method gives a higher level of confidence in the reservoir model produced. Interpolation of porosity and permeability data with minimum error and high accuracy is, therefore, essential in reservoir modeling. The most widely used interpolation algorithm, kriging, with enough well data is the best linear unbiased estimator. This research sought to compare the applicability and competitiveness of inverse distance weighting (IDW) method using power index of 1, 2 and 4 to kriging wh
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