Buchumschlag

Are Made and Missed Different? An analysis of Field Goal Attempts of Professional Basketball Players via Depth Based Testing Procedure

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Qi, Kai, Hu, Guanyu, Wu, Wei
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Applications Methodology
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

What Influences the Field Goal Attempts of Professional Players? Analysis of Basketball Shot Charts via Log Gaussian Cox Processes with Spatially Varying Coefficients
von: Cao, Jiahao, et al.
Veröffentlicht: (2025)

How do the professional players select their shot locations? An analysis of Field Goal Attempts via Bayesian Additive Regression Trees
von: Cao, Jiahao, et al.
Veröffentlicht: (2025)

Establishing the Parallels and Differences Between Right-Censored and Missing Covariates
von: Vazquez, Jesus E., et al.
Veröffentlicht: (2024)

How Much Does Home Field Advantage Matter in Soccer Games? A Causal Inference Approach for English Premier League Analysis
von: Wang, Chen, et al.
Veröffentlicht: (2022)

Difference-in-differences Design with Outcomes Missing Not at Random
von: Shin, Sooahn
Veröffentlicht: (2024)

Bayesian Spatially Clustered Compositional Regression: Linking intersectoral GDP contributions to Gini Coefficients
von: Meng, Jingcheng, et al.
Veröffentlicht: (2024)

Mixture of Finite Mixtures Model for Basket Trial
von: Geng, Junxian, et al.
Veröffentlicht: (2020)

Modeling Missing at Random Neuropsychological Test Scores Using a Mixture of Binomial Product Experts
von: Suen, Daniel, et al.
Veröffentlicht: (2023)

Causal Inference with Outcomes Truncated by Death and Missing Not at Random
von: Li, Wei, et al.
Veröffentlicht: (2024)

Single Changepoint Procedures
von: Lund, Robert, et al.
Veröffentlicht: (2025)

Depth-Based Local Center Clustering: A Framework for Handling Different Clustering Scenarios
von: Wang, Siyi, et al.
Veröffentlicht: (2025)

A Comparative Evaluation of a Conditional Median-Based Bayesian Growth Curve Modeling Approach with Missing Data
von: Tang, Dandan, et al.
Veröffentlicht: (2025)

Model Selection for Causal Modeling in Missing Exposure Problems
von: Shi, Yuliang, et al.
Veröffentlicht: (2024)

Analysis of Linked Files: A Missing Data Perspective
von: Kamat, Gauri, et al.
Veröffentlicht: (2024)

Correspondence analysis: handling cell-wise outliers via the reconstitution algorithm
von: Qi, Qianqian, et al.
Veröffentlicht: (2024)

Adjusting for Selection Bias Due to Missing Eligibility Criteria in Emulated Target Trials
von: Benz, Luke, et al.
Veröffentlicht: (2024)

Generalizing Trimming Bounds for Endogenously Missing Outcome Data Using Random Forests
von: Samii, Cyrus, et al.
Veröffentlicht: (2023)

Variational Bayesian Multiple Imputation in High-Dimensional Regression Models With Missing Responses
von: Li, Qiushuang, et al.
Veröffentlicht: (2025)

Correcting for Missing Data When Evaluating Surrogate Markers in a Clinical Trial
von: Lotspeich, Sarah C., et al.
Veröffentlicht: (2026)

Bayesian Bootstrap based Gaussian Copula Model for Mixed Data with High Missing Rates
von: Kim, Seongmin, et al.
Veröffentlicht: (2025)

Inverse Probability Weighting of Count Exposures in the Presence of Missing Data: A Simulation Study
von: Danka, Martin N., et al.
Veröffentlicht: (2026)

Multidimensional Stochastic Dominance Test Based on Center-outward Quantiles
von: Ma, Yiming, et al.
Veröffentlicht: (2025)

Outcome-Assisted Multiple Imputation of Missing Treatments
von: Feldman, Joseph, et al.
Veröffentlicht: (2025)

Robust Emax Model Fitting: Addressing Nonignorable Missing Binary Outcome in Dose-Response Analysis
von: Zhang, Jiangshan, et al.
Veröffentlicht: (2024)

Accounting for Missing Data in Public Health Research Using a Synthesis of Statistical and Mathematical Models
von: Zivich, Paul N, et al.
Veröffentlicht: (2025)

A Bayesian Hierarchical Generalization of Empirical Bayes for Crash Rate Estimation with Missing Traffic Volume
von: Skaug, Lars
Veröffentlicht: (2026)

On the Consistency of Bayesian Adaptive Testing under the Rasch Model
von: Yang, Hau-Hung, et al.
Veröffentlicht: (2024)

Scalable Causal Structure Learning via Amortized Conditional Independence Testing
von: Leiner, James, et al.
Veröffentlicht: (2023)

Sparse group principal component analysis via double thresholding with application to multi-cellular programs
von: Xu, Qi, et al.
Veröffentlicht: (2026)

Imputation of Nonignorable Missing Data in Surveys Using Auxiliary Margins Via Hot Deck and Sequential Imputation
von: Yang, Yanjiao, et al.
Veröffentlicht: (2024)

False Discovery Rate Control via Data Splitting for Testing-after-Clustering
von: Wang, Lijun, et al.
Veröffentlicht: (2024)

Randomization Tests for Distributions of Individual Treatment Effects via Combined Rank Statistics
von: Kim, David, et al.
Veröffentlicht: (2026)

Randomization Inference for Before-and-After Studies with Multiple Units: An Application to a Criminal Procedure Reform in Uruguay
von: Cattaneo, Matias D., et al.
Veröffentlicht: (2024)

Cumulative Logit Ordinal Regression with Proportional Odds under Nonignorable Missing Response -- Application to Phase III Trial
von: Maity, Arnab Kumar, et al.
Veröffentlicht: (2025)

Constructing a T-test for Value Function Comparison of Individualized Treatment Regimes in the Presence of Multiple Imputation for Missing Data
von: Lu, Minxin, et al.
Veröffentlicht: (2023)

Robust inference for the unification of confidence intervals in meta-analysis
von: Liang, Wei, et al.
Veröffentlicht: (2024)

Truncated Cauchy Combination Test: a Robust and Powerful P-value Combination Method with Arbitrary Correlations
von: Chen, Bo, et al.
Veröffentlicht: (2025)

Meta-analysis of Censored Adverse Events
von: Qi, Xinyue, et al.
Veröffentlicht: (2021)

Difference-in-Differences under Bipartite Network Interference: A Framework for Quasi-Experimental Assessment of the Effects of Environmental Policies on Health
von: Chen, Kevin L., et al.
Veröffentlicht: (2024)

Spatially Robust Inference with Predicted and Missing at Random Labels
von: Salerno, Stephen, et al.
Veröffentlicht: (2026)