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More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated.
While much has been published on the application of multiple imputation to epidemiological studies, there is limited literature that deals with model building in the presence of missing data, and more specifically model building including interactions.
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Since the context is the specification-based, more specifically model-based testing, we model the applications used in this work as Labeled Transition Systems (LTS).
This strategy offers the opportunity to improve models of pollen release and deposition and, more specifically, models of lepidopteran larval exposure to toxic Bt pollen and its subsequent effects.
In this paper we have chosen to use hierarchical Bayesian models, more specifically a model based on Besag, York and Mollié [ 55, 56] (BYM) to analyze the relationship between mortality and small-area deprivation.
This can be achieved by using generalized linear mixed modeling or, more specifically, multilevel modeling, which is also called hierarchical linear modeling, mixed-effects modeling, random-effects modeling, and others (see Barkaoui, 2013, 2014 and Cunnings, 2012, for other features and advantages of this method).
More specifically, the model involves emotion generation and integrates models for the emotion regulation strategies reappraisal, expressive suppression, and situation modification.
More specifically, this model is given by starting from the heteroscedastic noise model that describes the linear relation between the expectation and variance of a RAW pixel and taking into account the non-linear effect of gamma correction.
More specifically, their model is based on 3GPP/LTE downlink specifications [14, 15] where both BSs and terminals implement an OFDM air interface.
More specifically, the model space is estimated in a subject-specific manner, and the use of random-effects BMS/BMA identifies consistent effects across all subjects irrespective of scanner.
Since the ESACS and ISAAC projects, Airbus and Onera have been investigating failure propagation models and more specifically AltaRica model-based safety analysis.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com