Guardado en:
| Autor principal: | Attallah, Mustafa |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2409.01295 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Causal generalized linear models via Pearson risk invariance
por: Polinelli, Alice, et al.
Publicado: (2024)
por: Polinelli, Alice, et al.
Publicado: (2024)
Efficient algorithms for the sensitivities of the Pearson correlation coefficient and its statistical significance to online data
por: Harary, Marc
Publicado: (2024)
por: Harary, Marc
Publicado: (2024)
Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
por: Fan, Jianqing, et al.
Publicado: (2023)
por: Fan, Jianqing, et al.
Publicado: (2023)
Critical issues with the Pearson's chi-square test
por: Gurvich, Vladimir, et al.
Publicado: (2025)
por: Gurvich, Vladimir, et al.
Publicado: (2025)
Pearson Chi-squared Conditional Randomization Test
por: Javanmard, Adel, et al.
Publicado: (2021)
por: Javanmard, Adel, et al.
Publicado: (2021)
Neyman-Pearson multiclass classification under label noise via empirical likelihood
por: Zhang, Qiong, et al.
Publicado: (2026)
por: Zhang, Qiong, et al.
Publicado: (2026)
Revamping Conformal Selection With Optimal Power: A Neyman--Pearson Perspective
por: Qin, Jing, et al.
Publicado: (2025)
por: Qin, Jing, et al.
Publicado: (2025)
Distributed Conditional Feature Screening via Pearson Partial Correlation with FDR Control
por: Pang, Naiwen, et al.
Publicado: (2024)
por: Pang, Naiwen, et al.
Publicado: (2024)
Neyman-Pearson Multi-class Classification via Cost-sensitive Learning
por: Tian, Ye, et al.
Publicado: (2021)
por: Tian, Ye, et al.
Publicado: (2021)
Beyond Neyman-Pearson: e-values enable hypothesis testing with a data-driven alpha
por: Grünwald, Peter
Publicado: (2022)
por: Grünwald, Peter
Publicado: (2022)
Tests for categorical data beyond Pearson: A distance covariance and energy distance approach
por: Castro-Prado, Fernando, et al.
Publicado: (2024)
por: Castro-Prado, Fernando, et al.
Publicado: (2024)
The extension of Pearson correlation coefficient, measuring noise, and selecting features
por: Salimi, Reza, et al.
Publicado: (2024)
por: Salimi, Reza, et al.
Publicado: (2024)
Non-zero block selector: A linear correlation coefficient measure for blocking-selection models
por: Liang, Weixiong, et al.
Publicado: (2024)
por: Liang, Weixiong, et al.
Publicado: (2024)
Comparing the Pearson and Spearman Correlation Coefficients Across Distributions and Sample Sizes: A Tutorial Using Simulations and Empirical Data
por: de Winter, J. C. F., et al.
Publicado: (2024)
por: de Winter, J. C. F., et al.
Publicado: (2024)
A joint model of correlated ordinal and continuous variables
por: Vana-Gür, Laura, et al.
Publicado: (2024)
por: Vana-Gür, Laura, et al.
Publicado: (2024)
Prediction modelling with many correlated and zero-inflated predictors: assessing a nonnegative garrote approach
por: Gregorich, Mariella, et al.
Publicado: (2024)
por: Gregorich, Mariella, et al.
Publicado: (2024)
Semi-analytic approximate stability selection for correlated data in generalized linear models
por: Takahashi, Takashi, et al.
Publicado: (2020)
por: Takahashi, Takashi, et al.
Publicado: (2020)
Robust variable selection for partially linear additive models
por: Boente, Graciela, et al.
Publicado: (2024)
por: Boente, Graciela, et al.
Publicado: (2024)
Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control
por: Liu, Lingchong, et al.
Publicado: (2025)
por: Liu, Lingchong, et al.
Publicado: (2025)
Quantifying uncertainty and stability among highly correlated predictors: a subspace perspective
por: Zhang, Xiaozhu, et al.
Publicado: (2025)
por: Zhang, Xiaozhu, et al.
Publicado: (2025)
Quantifying total correlations in quantum systems through the Pearson correlation coefficient
por: Tserkis, Spyros, et al.
Publicado: (2023)
por: Tserkis, Spyros, et al.
Publicado: (2023)
On the statistical analysis of grouped data: when Pearson $χ^2$ and other divisible statistics are not goodness-of-fit tests
por: Algeri, Sara, et al.
Publicado: (2024)
por: Algeri, Sara, et al.
Publicado: (2024)
A robust estimation and variable selection approach for sparse partially linear additive models
por: Martínez, Alejandra Mercedes
Publicado: (2025)
por: Martínez, Alejandra Mercedes
Publicado: (2025)
How to quantify direct correlations between variables
por: Wu, Shengjun, et al.
Publicado: (2026)
por: Wu, Shengjun, et al.
Publicado: (2026)
Doubly robust and computationally efficient high-dimensional variable selection
por: Chakraborty, Abhinav, et al.
Publicado: (2024)
por: Chakraborty, Abhinav, et al.
Publicado: (2024)
Path-specific causal decomposition analysis with multiple correlated mediator variables
por: Smith, Melissa J., et al.
Publicado: (2023)
por: Smith, Melissa J., et al.
Publicado: (2023)
Modeling double bounded data based on correlated gamma random variables
por: Vila, Roberto, et al.
Publicado: (2026)
por: Vila, Roberto, et al.
Publicado: (2026)
Semi-parametric local variable selection under misspecification
por: Rossell, David, et al.
Publicado: (2023)
por: Rossell, David, et al.
Publicado: (2023)
Commentary on critique and rebuttal of ‘On the pixel selection criterion for the calculation of the Pearson's correlation coefficient in fluorescence microscopy’
por: Fabrice Cordelieres, et al.
Publicado: (2025)
por: Fabrice Cordelieres, et al.
Publicado: (2025)
Adaptive greedy forward variable selection for linear regression models with incomplete data using multiple imputation
por: Lee, Yong-Shiuan
Publicado: (2022)
por: Lee, Yong-Shiuan
Publicado: (2022)
Individualized treatment regimens under correlated data with multiple outcomes
por: Dolmatov, Misha, et al.
Publicado: (2025)
por: Dolmatov, Misha, et al.
Publicado: (2025)
A generalized Bayesian approach for high-dimensional robust regression with serially correlated errors and predictors
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
por: Chakraborty, Saptarshi, et al.
Publicado: (2024)
Distributed variable screening for generalized linear models
por: Diao, Tianbo, et al.
Publicado: (2024)
por: Diao, Tianbo, et al.
Publicado: (2024)
A graphical framework for interpretable correlation matrix models
por: Sterrantino, Anna Freni, et al.
Publicado: (2023)
por: Sterrantino, Anna Freni, et al.
Publicado: (2023)
Comparison study of variable selection procedures in high-dimensional Gaussian linear regression
por: Lacroix, Perrine, et al.
Publicado: (2021)
por: Lacroix, Perrine, et al.
Publicado: (2021)
On the minimum information checkerboard copulas under fixed Kendall's rank correlation
por: Sukeda, Issey, et al.
Publicado: (2023)
por: Sukeda, Issey, et al.
Publicado: (2023)
A nutritionally informed model for Bayesian variable selection with metabolite response variables
por: Clark-Boucher, Dylan, et al.
Publicado: (2025)
por: Clark-Boucher, Dylan, et al.
Publicado: (2025)
inlabru: software for fitting latent Gaussian models with non-linear predictors
por: Lindgren, Finn, et al.
Publicado: (2024)
por: Lindgren, Finn, et al.
Publicado: (2024)
Variance-based sensitivity analysis in the presence of correlated input variables
por: Most, Thomas
Publicado: (2024)
por: Most, Thomas
Publicado: (2024)
A spatial-correlated multitask linear mixed-effects model for imaging genetics
por: Pu, Zhibin, et al.
Publicado: (2024)
por: Pu, Zhibin, et al.
Publicado: (2024)
Ejemplares similares
-
Causal generalized linear models via Pearson risk invariance
por: Polinelli, Alice, et al.
Publicado: (2024) -
Efficient algorithms for the sensitivities of the Pearson correlation coefficient and its statistical significance to online data
por: Harary, Marc
Publicado: (2024) -
Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification
por: Fan, Jianqing, et al.
Publicado: (2023) -
Critical issues with the Pearson's chi-square test
por: Gurvich, Vladimir, et al.
Publicado: (2025) -
Pearson Chi-squared Conditional Randomization Test
por: Javanmard, Adel, et al.
Publicado: (2021)