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Spatial Performance Indicators and Graphs in Basketball

Social indicators research, 2021-08, Vol.156 (2-3), p.725-738

2021

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Basketball Data Science: With Applications in R

1st, 2020

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Ordinal Data Models for No-Opinion Responses in Attitude Survey

Sociological methods & research, 2020-02, Vol.49 (1), p.250-276

2020

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Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game

Advances in statistical analysis : AStA : a journal of the German Statistical Society, 2023, Vol.107 (1-2), p.271-293

2023

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Modeling “don’t know” responses in rating scales

Pattern recognition letters, 2014-08, Vol.45, p.226-234

2014

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Modeling rating data with Nonlinear CUB models

Computational statistics & data analysis, 2014-10, Vol.78, p.100-118

2014

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Spatial performance analysis in basketball with CART, random forest and extremely randomized trees

Annals of operations research, 2023-06, Vol.325 (1), p.495-519

2023

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A mixture model for ordinal variables measured on semantic differential scales

Econometrics and statistics, 2022-04, Vol.22, p.98-123

2022

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Identifying the Component Structure of Satisfaction Scales by Nonlinear Principal Components Analysis

Quality technology & quantitative management, 2010-01, Vol.7 (2), p.97-115

2010

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Markov switching modelling of shooting performance variability and teammate interactions in basketball

Journal of the Royal Statistical Society Series C: Applied Statistics, 2020-11, Vol.69 (5), p.1337-1356

2020

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Statistical models for classification by handedness of Olympic Trap shooters in digital training services and remote coaching

Computational statistics, 2024-10

2024

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Discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo and Rosaria Simone

Statistical methods & applications, 2019-09, Vol.28 (3), p.465-470

2019

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Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions

International journal of sports science & coaching, 2018-08, Vol.13 (4), p.569-589

2018

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Identifiability of a model for discrete frequency distributions with a multidimensional parameter space

Journal of multivariate analysis, 2015-09, Vol.140, p.302-316

2015

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Estimation of nonlinear CUB models via numerical optimization and EM algorithm

Communications in statistics. Simulation and computation, 2017-08, Vol.46 (7), p.5723-5739

2017

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Scoring probability maps in the basketball court with Indicator Kriging estimation

Computational statistics, 2024-11

2024

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A Mixture Model for the Analysis of Categorical Variables Measured on Five-point Semantic Differential Scales

Österreichische Zeitschrift für Statistik, 2024-06, Vol.53 (3), p.70-86

2024

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On the equivalence of two mixture models for rating data

Advances in statistical analysis : AStA : a journal of the German Statistical Society, 2024-10

2024

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Modelling the dynamic pattern of surface area in basketball and its effects on team performance

Journal of quantitative analysis in sports, 2018-09, Vol.14 (3), p.117-130

2018

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Alley‐oop! Basketball analytics in R

Significance (Oxford, England), 2021-04, Vol.18 (2), p.26-31

2021

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Treatment of ‘don’t know’ responses in a mixture model for rating data

Metron (Rome), 2016-04, Vol.74 (1), p.99-115

2016

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Clustering ranking data in market segmentation: a case study on the Italian McDonald's customers' preferences

Journal of applied statistics, 2016-08, Vol.43 (11), p.1959-1976

2016

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Treatment of “don’t know” responses in the consumers’ perceptions about sustainability in the agri-food sector

Quality & quantity, 2017-03, Vol.51 (2), p.765-778

2017

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On the Imputation of Missing Data in Surveys with Likert-Type Scales

Journal of classification, 2011-04, Vol.28 (1), p.93-112

2011

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Guest Editorial ‘Statistical Modelling for Sports Analytics’

Statistical modelling, 2018-12, Vol.18 (5-6), p.385-387

2018

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Spatial Performance Indicators and Graphs in Basketball

Basketball Data Science: With Applications in R

Ordinal Data Models for No-Opinion Responses in Attitude Survey

Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game

Modeling “don’t know” responses in rating scales

Modeling rating data with Nonlinear CUB models

Spatial performance analysis in basketball with CART, random forest and extremely randomized trees

A mixture model for ordinal variables measured on semantic differential scales

Identifying the Component Structure of Satisfaction Scales by Nonlinear Principal Components Analysis

Markov switching modelling of shooting performance variability and teammate interactions in basketball

Statistical models for classification by handedness of Olympic Trap shooters in digital training services and remote coaching

Discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo and Rosaria Simone

Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions

Identifiability of a model for discrete frequency distributions with a multidimensional parameter space

Estimation of nonlinear CUB models via numerical optimization and EM algorithm

Scoring probability maps in the basketball court with Indicator Kriging estimation

A Mixture Model for the Analysis of Categorical Variables Measured on Five-point Semantic Differential Scales

On the equivalence of two mixture models for rating data

Modelling the dynamic pattern of surface area in basketball and its effects on team performance

Alley‐oop! Basketball analytics in R

Treatment of ‘don’t know’ responses in a mixture model for rating data

Clustering ranking data in market segmentation: a case study on the Italian McDonald's customers' preferences

Treatment of “don’t know” responses in the consumers’ perceptions about sustainability in the agri-food sector

On the Imputation of Missing Data in Surveys with Likert-Type Scales

Guest Editorial ‘Statistical Modelling for Sports Analytics’

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