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Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID-19 infection

Scientific reports, 2023-01, Vol.13 (1), p.900-900, Article 900

2023

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Publisher Correction: Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID‑19 infection

Scientific reports, 2023-01, Vol.13 (1), p.1776-1776, Article 1776

2023

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Multivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimators

Statistical papers (Berlin, Germany), 2021-08, Vol.62 (4), p.1583-1609

2021

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Towards a mathematical framework to inform neural network modelling via polynomial regression

Neural networks, 2021-10, Vol.142, p.57-72

2021

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The Mahalanobis Distance for Functional Data With Applications to Classification

Technometrics, 2015-04, Vol.57 (2), p.281-291

2015

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Accurate Prediction of Children's ADHD Severity Using Family Burden Information: A Neural Lasso Approach

Frontiers in computational neuroscience, 2021-06, Vol.15, p.674028-674028

2021

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NN2Poly: A Polynomial Representation for Deep Feed-Forward Artificial Neural Networks

IEEE transaction on neural networks and learning systems, 2023-11, Vol.PP, p.1-15

2023

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Estimating the COVID-19 Prevalence in Spain With Indirect Reporting via Open Surveys

Frontiers in public health, 2021-04, Vol.9, p.658544-658544

2021

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A Kendall correlation coefficient between functional data

Advances in data analysis and classification, 2019-12, Vol.13 (4), p.1083-1103

2019

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Robust regression based on shrinkage with application to Living Environment Deprivation

Stochastic environmental research and risk assessment, 2020-02, Vol.34 (2), p.293-310

2020

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Fitting procedure for the two-state Batch Markov modulated Poisson process

European journal of operational research, 2019-11, Vol.279 (1), p.79-92

2019

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A fast epigraph and hypograph-based approach for clustering functional data

Statistics and computing, 2023-04, Vol.33 (2), Article 36

2023

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Functional outlier detection by a local depth with application to NO x levels

Stochastic environmental research and risk assessment, 2016-04, Vol.30 (4), p.1115-1130

2016

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Adaptive sparse group LASSO in quantile regression

Advances in data analysis and classification, 2021-09, Vol.15 (3), p.547-573

2021

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A bivariate two-state Markov modulated Poisson process for failure modeling

Reliability engineering & system safety, 2021-04, Vol.208, p.107318, Article 107318

2021

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On the estimation of extreme directional multivariate quantiles

Communications in statistics. Theory and methods, 2020-11, Vol.49 (22), p.5504-5534

2020

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An Iterative Sparse-Group Lasso

Journal of computational and graphical statistics, 2019-07, Vol.28 (3), p.722-731

2019

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Allocation Policies of Redundancies in Two-Parallel-Series and Two-Series-Parallel Systems

IEEE transactions on reliability, 2014-03, Vol.63 (1), p.223-229

2014

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A directional multivariate value at risk

Insurance, mathematics & economics, 2015-11, Vol.65, p.111-123

2015

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A twist in Intimate Partner Violence Risk Assessment Tools: Gauging the contribution of exogenous and historical variables

Knowledge-based systems, 2021-12, Vol.234, p.107586, Article 107586

2021

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Detecting and classifying outliers in big functional data

Advances in data analysis and classification, 2022-09, Vol.16 (3), p.725-760

2022

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Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models

Statistical papers (Berlin, Germany), 2023-02, Vol.64 (1), p.227-253

2023

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Failure modeling of an electrical N-component framework by the non-stationary Markovian arrival process

Reliability engineering & system safety, 2015-02, Vol.134, p.126-133

2015

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STOCHASTIC COMPARISONS OF NONHOMOGENEOUS PROCESSES

Probability in the engineering and informational sciences, 2001-04, Vol.15 (2), p.199-224, Article S0269964801152058

2001

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Variable selection with P‐splines in functional linear regression: Application in graft‐versus‐host disease

Biometrical journal, 2020-11, Vol.62 (7), p.1670-1686

2020

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Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID-19 infection

Publisher Correction: Using survey data to estimate the impact of the omicron variant on vaccine efficacy against COVID‑19 infection

Multivariate outlier detection based on a robust Mahalanobis distance with shrinkage estimators

Towards a mathematical framework to inform neural network modelling via polynomial regression

The Mahalanobis Distance for Functional Data With Applications to Classification

Accurate Prediction of Children's ADHD Severity Using Family Burden Information: A Neural Lasso Approach

NN2Poly: A Polynomial Representation for Deep Feed-Forward Artificial Neural Networks

Estimating the COVID-19 Prevalence in Spain With Indirect Reporting via Open Surveys

A Kendall correlation coefficient between functional data

Robust regression based on shrinkage with application to Living Environment Deprivation

Fitting procedure for the two-state Batch Markov modulated Poisson process

A fast epigraph and hypograph-based approach for clustering functional data

Functional outlier detection by a local depth with application to NO x levels

Adaptive sparse group LASSO in quantile regression

A bivariate two-state Markov modulated Poisson process for failure modeling

On the estimation of extreme directional multivariate quantiles

An Iterative Sparse-Group Lasso

Allocation Policies of Redundancies in Two-Parallel-Series and Two-Series-Parallel Systems

A directional multivariate value at risk

A twist in Intimate Partner Violence Risk Assessment Tools: Gauging the contribution of exogenous and historical variables

Detecting and classifying outliers in big functional data

Group linear algorithm with sparse principal decomposition: a variable selection and clustering method for generalized linear models

Failure modeling of an electrical N-component framework by the non-stationary Markovian arrival process

STOCHASTIC COMPARISONS OF NONHOMOGENEOUS PROCESSES

Variable selection with P‐splines in functional linear regression: Application in graft‐versus‐host disease

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