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Modelling behavioural interactions of drivers' in mixed traffic conditions
Journal of Traffic and Transportation Engineering (English ed. Online), 2018 Mixed traffic conditions are often prevalent in developing economies such as India, China, Bangladesh, etc. and are characterised by the presence of multiple vehicle types.
Caleb Ronald Munigety
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Robust MM-Estimation and Inference in Mixed Linear Models [PDF]
Mixed linear models are used to analyse data in many settings. These models generally rely on the normality assumption and are often fitted by means of the maximum likelihood estimator (MLE) or the restricted maximum likelihood estimator (REML). However,
Samuel Copt, Stephane Heritier
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Two Approaches to Imputation and Adjustment of Air Quality Data from a Composite Monitoring Network [PDF]
, 2009 An analysis of air quality data is provided for the municipal area of Taranto characterized by high environmental risks, due to the massive presence of industrial sites with elevated environmental impact activities.
JONA LASINIO, Giovanna, Pollice, A.
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Genome BiologyDynamic lineage tracing technologies combine genome editing with single-cell sequencing to track cell divisions. We introduce Lineage Analysis via Maximum Likelihood (LAML) to infer a maximum likelihood time-resolved cell lineage tree under the ...
Gillian Chu +3 more
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Choosing hybrid organizations for local servicesdelivery: An empirical analysis of partial privatization [PDF]
The empirical literature about factors explaining local government delivery choices has traditionally focused the attention on the public or private production dilemma.
Germa Bel, Xavier Fageda
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Clustering Longitudinal Mixed-type Data
A model-based clustering algorithm is presented to cluster longitudinal mixed data. Assuming that the non-continuous variables are the discretization of underlying latent continuous variables, the model relies on a mixture of matrix-variate normal distributions, accounting simultaneously for within- and between-time dependence structures.
Amato, Francesco, Jacques, Julien
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Clustering large mixed-type data with ordinal variables
Advances in Data Analysis and ClassificationAbstract One of the most frequently used algorithms for clustering data with both numeric and categorical variables is the k-prototypes algorithm, an extension of the well-known k-means clustering. Gower’s distance denotes another popular approach for dealing with mixed-type data and is suitable not only for numeric and categorical but also ...
Gero Szepannek +2 more
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Learning Bayesian Networks: A Copula Approach for Mixed-Type Data
PsychometrikaEstimating dependence relationships between variables is a crucial issue in many applied domains and in particular psychology. When several variables are entertained, these can be organized into a network which encodes their set of conditional dependence relations.
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The Impact of Diabetes and Metabolic Syndrome Burden on Pain, Neuropathy Severity and Fiber Type
Annals of Clinical and Translational NeurologyObjective Determine the association between diabetes and metabolic syndrome (MetS) burden (number of MetS criteria fulfilled) and pain, neuropathy severity, and fiber type involvement in individuals with established polyneuropathy. Methods The Peripheral
Long Davalos +13 more
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Mixed-type data augmentations for environmental sound classification
, 2023 The goal of environmental sound classification is to accurately identify and classify sounds in order to provide valuable insights about the environment. The classification task can be solved by training machine learning models, such as convolutional neural networks, on a dataset of labeled sound samples.
Turskis, Tadas +3 more
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