Gradient-Boosted Pseudo-Weighting: Methods for Population Inference from Nonprobability samples
Fuente:
arXiv
Guardado en:
| Autores principales: | Liu, Kangrui, Wang, Lingxiao, Li, Yan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Thresholding Nonprobability Units in Combined Data for Efficient Domain Estimation
por: Savitsky, Terrance D., et al.
Publicado: (2025)
por: Savitsky, Terrance D., et al.
Publicado: (2025)
Pseudo-Empirical Likelihood Methods for Causal Inference
por: Huang, Jingyue, et al.
Publicado: (2024)
por: Huang, Jingyue, et al.
Publicado: (2024)
Using Model-Assisted Calibration Methods to Improve Efficiency of Regression Analyses with Two-Phase Samples under Complex Survey Designs
por: Wang, Lingxiao
Publicado: (2023)
por: Wang, Lingxiao
Publicado: (2023)
Statistical Inference for Gradient Boosting Regression
por: Fang, Haimo, et al.
Publicado: (2025)
por: Fang, Haimo, et al.
Publicado: (2025)
Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
por: Pashley, Nicole E.
Publicado: (2019)
por: Pashley, Nicole E.
Publicado: (2019)
Pseudo Empirical Likelihood Inference for Non-Probability Survey Samples
por: Chen, Yilin, et al.
Publicado: (2025)
por: Chen, Yilin, et al.
Publicado: (2025)
Estimating Heterogeneous Treatment Effects for Spatio-Temporal Causal Inference
por: Zhou, Lingxiao, et al.
Publicado: (2024)
por: Zhou, Lingxiao, et al.
Publicado: (2024)
Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference
por: Yao, Minhao, et al.
Publicado: (2025)
por: Yao, Minhao, et al.
Publicado: (2025)
RieszBoost: Gradient Boosting for Riesz Regression
por: Lee, Kaitlyn J., et al.
Publicado: (2025)
por: Lee, Kaitlyn J., et al.
Publicado: (2025)
Leveraging Relational Evidence: Population Size Estimation on Tree-Structured Data with the Weighted Multiplier Method
por: Flynn, Mallory J, et al.
Publicado: (2025)
por: Flynn, Mallory J, et al.
Publicado: (2025)
Gradient Boosting for Hierarchical Data in Small Area Estimation
por: Messer, Paul, et al.
Publicado: (2024)
por: Messer, Paul, et al.
Publicado: (2024)
Deep Neural Networks for Doubly Robust Estimation with Nonprobability Survey Samples
por: Dai, Yufang, et al.
Publicado: (2026)
por: Dai, Yufang, et al.
Publicado: (2026)
A Random Forest Inverse Probability Weighted Pseudo-Observation Framework for Alternating Recurrent Events
por: Loe, Abigail, et al.
Publicado: (2025)
por: Loe, Abigail, et al.
Publicado: (2025)
Bayesian inference for aggregated Hawkes processes
por: Zhou, Lingxiao, et al.
Publicado: (2022)
por: Zhou, Lingxiao, et al.
Publicado: (2022)
Distributed Pseudo-Likelihood Method for Community Detection in Large-Scale Networks
por: Deng, Jiayi, et al.
Publicado: (2024)
por: Deng, Jiayi, et al.
Publicado: (2024)
Balancing Weights for Causal Inference in Observational Factorial Studies
por: Yu, Ruoqi, et al.
Publicado: (2023)
por: Yu, Ruoqi, et al.
Publicado: (2023)
Statistical Inference on Gradient Flows
por: Li, Tongyu, et al.
Publicado: (2026)
por: Li, Tongyu, et al.
Publicado: (2026)
Enhancing Inference for Small Cohorts via Transfer Learning and Weighted Integration of Multiple Datasets
por: Guha, Subharup, et al.
Publicado: (2025)
por: Guha, Subharup, et al.
Publicado: (2025)
Gradient-Boosted Generalized Linear Models for Conditional Vine Copulas
por: Jobst, David, et al.
Publicado: (2024)
por: Jobst, David, et al.
Publicado: (2024)
lmw: Linear Model Weights for Causal Inference
por: Chattopadhyay, Ambarish, et al.
Publicado: (2023)
por: Chattopadhyay, Ambarish, et al.
Publicado: (2023)
What is Overlap Weighting, How Has it Evolved, and When to Use It for Causal Inference?
por: Lu, Haidong, et al.
Publicado: (2026)
por: Lu, Haidong, et al.
Publicado: (2026)
Gradient-bridged Posterior: Bayesian Inference for Models with Implicit Functions
por: Zeng, Cheng, et al.
Publicado: (2025)
por: Zeng, Cheng, et al.
Publicado: (2025)
Post-Hoc Inference of Cross-Classified Statistics from Hierarchical Bayes Survey Weights
por: Tam, Siu-Ming
Publicado: (2026)
por: Tam, Siu-Ming
Publicado: (2026)
Addressing Positivity Violations in Extending Inference to a Target Population
por: Lu, Jun, et al.
Publicado: (2024)
por: Lu, Jun, et al.
Publicado: (2024)
Weight a Minute: Understanding Variability in PATE Estimates Across Target Populations
por: Stewart, William, et al.
Publicado: (2025)
por: Stewart, William, et al.
Publicado: (2025)
Scalable Efficient Inference in Complex Surveys through Targeted Resampling of Weights
por: Das, Snigdha, et al.
Publicado: (2025)
por: Das, Snigdha, et al.
Publicado: (2025)
Target Aggregate Data Adjustment Method for Transportability Analysis Utilizing Summary-Level Data from the Target Population
por: Yan, Yichen, et al.
Publicado: (2024)
por: Yan, Yichen, et al.
Publicado: (2024)
Statistical inference for large-dimensional tensor factor model by iterative projections
por: Barigozzi, Matteo, et al.
Publicado: (2022)
por: Barigozzi, Matteo, et al.
Publicado: (2022)
Gradient Boosting for Spatial Panel Models with Random and Fixed Effects
por: Balzer, Michael, et al.
Publicado: (2026)
por: Balzer, Michael, et al.
Publicado: (2026)
Gradient-Based Approximate Bayesian Inference with Entropy-Optimized Summary Statistics for Compartmental Models
por: Li, Xiahui, et al.
Publicado: (2024)
por: Li, Xiahui, et al.
Publicado: (2024)
Weighted least squares estimation by multivariate-dependent weights for linear regression models
por: Huang, Lei, et al.
Publicado: (2026)
por: Huang, Lei, et al.
Publicado: (2026)
A Unified Inference Method for FROC-type Curves and Related Summary Indices
por: Sun, Jiarui, et al.
Publicado: (2025)
por: Sun, Jiarui, et al.
Publicado: (2025)
A New Method for Multinomial Inference using Dempster-Shafer Theory
por: Lawrence, Earl C., et al.
Publicado: (2024)
por: Lawrence, Earl C., et al.
Publicado: (2024)
On the Utility of Equal Batch Sizes for Inference in Stochastic Gradient Descent
por: Singh, Rahul, et al.
Publicado: (2023)
por: Singh, Rahul, et al.
Publicado: (2023)
Sample Empirical Likelihood Methods for Causal Inference
por: Huang, Jingyue, et al.
Publicado: (2024)
por: Huang, Jingyue, et al.
Publicado: (2024)
Wasserstein Gradient Boosting: A Framework for Distribution-Valued Supervised Learning
por: Matsubara, Takuo
Publicado: (2024)
por: Matsubara, Takuo
Publicado: (2024)
Forest Kernel Balancing Weights: Outcome-Guided Features for Causal Inference
por: Shen, Andy A., et al.
Publicado: (2025)
por: Shen, Andy A., et al.
Publicado: (2025)
Repro Samples Method for a Performance Guaranteed Inference in General and Irregular Inference Problems
por: Xie, Minge, et al.
Publicado: (2024)
por: Xie, Minge, et al.
Publicado: (2024)
Repro Samples Method for Model-Free Inference in High-Dimensional Binary Classification
por: Hou, Xiaotian, et al.
Publicado: (2025)
por: Hou, Xiaotian, et al.
Publicado: (2025)
Finite Population Sampling as n to N: Empirical Evidence for the Transition from Inference to Accuracy
por: Crowhurst, Mike
Publicado: (2026)
por: Crowhurst, Mike
Publicado: (2026)
Ejemplares similares
-
Thresholding Nonprobability Units in Combined Data for Efficient Domain Estimation
por: Savitsky, Terrance D., et al.
Publicado: (2025) -
Pseudo-Empirical Likelihood Methods for Causal Inference
por: Huang, Jingyue, et al.
Publicado: (2024) -
Using Model-Assisted Calibration Methods to Improve Efficiency of Regression Analyses with Two-Phase Samples under Complex Survey Designs
por: Wang, Lingxiao
Publicado: (2023) -
Statistical Inference for Gradient Boosting Regression
por: Fang, Haimo, et al.
Publicado: (2025) -
Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
por: Pashley, Nicole E.
Publicado: (2019)