Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition [PDF]
Atmospheric Measurement Techniques, 2021 Global high-resolution observations of atmospheric composition from satellites can greatly improve our understanding of surface emissions through inverse analyses.
H. Nesser +7 more
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Reduced Rank Models for Contingency Tables [PDF]
Biometrika, 1991 SUMMARY Reduced rank models for the analysis of two-way contingency tables are introduced. Two classes of reduced rank models are discerned, with well-known exponents canonical analysis and latent class analysis. The relation between these two classes is discussed.
Jan de Leeuw, Peter van der Heijden
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Concurrent ordination: Simultaneous unconstrained and constrained latent variable modelling
Methods in Ecology and Evolution, 2023 In community ecology, unconstrained ordination can be used to indirectly explore drivers of community composition, while constrained ordination can be used to directly relate predictors to an ecological community. However, existing constrained ordination
Bert van derVeen +3 more
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Obstacles and benefits of the implementation of a reduced-rank smoother with a high resolution model of the tropical Atlantic Ocean [PDF]
Ocean Science, 2012 Most of oceanographic operational centers use three-dimensional data assimilation schemes to produce reanalyses. We investigate here the benefits of a smoother, i.e. a four-dimensional formulation of statistical assimilation.
N. Freychet +4 more
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The SAR Model for Very Large Datasets: A Reduced Rank Approach
Econometrics, 2015 The SAR model is widely used in spatial econometrics to model Gaussian processes on a discrete spatial lattice, but for large datasets, fitting it becomes computationally prohibitive, and hence, its usefulness can be limited.
Sandy Burden +2 more
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Estimation of genetic parameters for test day records of dairy traits in the first three lactations
Genetics Selection Evolution, 2005 Application of test-day models for the genetic evaluation of dairy populations requires the solution of large mixed model equations. The size of the (co)variance matrices required with such models can be reduced through the use of its first eigenvectors.
Ducrocq Vincent +2 more
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Model diagnostics in reduced-rank estimation [PDF]
Statistics and Its Interface, 2016 Reduced-rank methods are very popular in high-dimensional multivariate analysis for conducting simultaneous dimension reduction and model estimation. However, the commonly-used reduced-rank methods are not robust, as the underlying reduced-rank structure can be easily distorted by only a few data outliers.
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Random generation of finitely generated subgroups of a free group [PDF]
, 2007 We give an efficient algorithm to randomly generate finitely generated subgroups of a given size, in a finite rank free group. Here, the size of a subgroup is the number of vertices of its representation by a reduced graph such as can be obtained by the ...
Cyril Nicaud +3 more
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Johansen’s Reduced Rank Estimator Is GMM
Econometrics, 2018 The generalized method of moments (GMM) estimator of the reduced-rank regression model is derived under the assumption of conditional homoscedasticity.
Bruce E. Hansen
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Model and Controller Order Reduction for Infinite Dimensional Systems [PDF]
ITB Journal of Engineering Science, 2010 This paper presents a reduced order model problem using reciprocal transformation and balanced truncation followed by low order controller design of infinite dimensional systems.
Fatmawati +3 more
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