ENSO-ASC 1.0.0: ENSO deep learning forecast model with a multivariate air–sea coupler [PDF]
Geoscientific Model Development, 2021 The El Niño–Southern Oscillation (ENSO) is an extremely complicated ocean–atmosphere coupling event, the development and decay of which are usually modulated by the energy interactions between multiple physical variables.
B. Mu, B. Qin, S. Yuan
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Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms [PDF]
, 2012 The paper extends existing models for multilevel multivariate data with mixed response types to handle quite general types and patterns of missing data values in a wide range of multilevel generalized linear models.
Browne, William J. +2 more
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Technical note: Changes in cross- and auto-dependence structures in climate projections of daily precipitation and their sensitivity to outliers [PDF]
Hydrology and Earth System Sciences, 2019 Simulations of regional or global climate models are often used for climate change impact assessment. To eliminate systematic errors, which are inherent to all climate model simulations, a number of post-processing (statistical downscaling) methods have ...
J. Hnilica +3 more
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Química Nova, 2008 The objective of this study was to develop and validate an analytical method for quantification of glucosamine and chondroitin in pharmaceutical formulations. Multivariate calibration combined with infrared spectrophotometry allowed this analysis.
Paula Rossignoli +4 more
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Remote Sensing, 2022 This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables.
Azbina Rahman +5 more
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Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model
, 2011 This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject ...
Alexandre G. Patriota +14 more
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Estimation with Numerical Integration on Sparse Grids [PDF]
, 2006 For the estimation of many econometric models, integrals without analytical solutions have to be evaluated. Examples include limited dependent variables and nonlinear panel data models.
Heiss, Florian, Winschel, Viktor
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Estimation for the Multivariate Errors-in-Variables Model with Estimated Error Covariance Matrix
The Annals of Statistics, 1984 The authors consider the estimation problem of multivariate errors-in- variables models. Let \(r\times 1\) row vectors \(y_ i\) and \(k\times 1\) row vectors \(x_ i\) satisfy \(y_ i=\beta_ 0+x_ i\beta\), \(i=1,2,...,n\), where \(\beta_ 0\) and \(\beta\) are 1\(\times r\) and \(k\times r\) matrices of parameters, respectively.
Amemiya, Yasuo, Fuller, Wayne A.
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, 2015 The Cramer-Rao lower bound for the estimation of the affine transformation parameters in a multivariate heteroscedastic errors-in-variables model is derived.
Cohen, E. A. K., Kim, D., Ober, R. J.
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Multivariate emulation of computer simulators: model selection and diagnostics with application to a humanitarian relief model [PDF]
, 2016 We present a common framework for Bayesian emulation methodologies for multivariate-output simulators, or computer models, that employ either parametric linear models or nonparametric Gaussian processes.
Overstall, Antony M., Woods, David C.
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