Results 31 to 40 of about 83,537 (273)
Construction Procurement: Modelling Bidders’ Learning in Recurrent Bidding [PDF]
, 2015 Construction remains a significant area of public expenditure. An understanding of the process of changes in construction pricing, and how the process can be manipulated through the release of bidding feedback information is vital, in order to best ...
Ling, Florence Yean Yng +2 more
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Entropy, 2020 The approximated non-linear least squares (ALS) tunes or calibrates the computer model by minimizing the squared error between the computer output and real observations by using an emulator such as a Gaussian process (GP) model. A potential defect of the
Yun Am Seo, Jeong-Soo Park
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Mean squared error of empirical predictor
, 2004 The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are ...
Das, Kalyan +2 more
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Indonesian Journal of Statistics and Its Applications, 2021 Small area estimation can be used to predict the population parameter with small sample sizes. For some cases, the population units that are close spatially may be more related than units that are further apart. The use of spatial information like geographic coordinates are studied in this research.
Naima Rakhsyanda +2 more
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Journal of Big Data, 2022 Background Acute lower respiratory infections (ALRI) are a major cause of mortality among children under five. This study aimed to investigate the spatiotemporal pattern of ALRI in Ethiopian administrative zones.
Meseret Tadesse Fetene +2 more
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Frontiers in Plant Science, 2023 Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to ...
Haizheng Xiong +5 more
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Local case-control sampling: Efficient subsampling in imbalanced data sets [PDF]
, 2014 For classification problems with significant class imbalance, subsampling can reduce computational costs at the price of inflated variance in estimating model parameters.
Fithian, William, Hastie, Trevor
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Strategies for Estimating Genetic Parameters in Marker-Assisted Best Linear Unbiased Predictor Models in Dairy Cattle [PDF]
Journal of Dairy Science, 2008 An appropriate strategy to estimate variance components and breeding values in genetic models with quantitative trait loci (QTL) was developed for a dairy cattle breeding scheme by utilizing simulated data. Reliable estimates for variance components in QTL models are a prerequisite in fine-mapping experiments and for marker-assisted genetic evaluations.
S, Neuner +3 more
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Ekonometria, 2020 The problem of small area prediction is considered under a Linear Mixed Model. The article presents a proposal of an empirical best linear unbiased predictor under a model with two correlated random effects.
Małgorzata K. Krzciuk
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Best linear unbiased estimation for varying probability with and without replacement sampling
Special Matrices, 2019 When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated.
Haslett Stephen
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