Pages that link to "Item:Q2194566"
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The following pages link to Models as approximations. I. Consequences illustrated with linear regression (Q2194566):
Displaying 19 items.
- Optimal selection of sample-size dependent common subsets of covariates for multi-task regression prediction (Q2074281) (← links)
- Some perspectives on inference in high dimensions (Q2075798) (← links)
- Dependence of variance on covariate design in nonparametric link regression (Q2105389) (← links)
- Maximum likelihood estimation for score-driven models (Q2116342) (← links)
- Analysis of odds, probability, and hazard ratios: from \(2\) by \(2\) tables to two-sample survival data (Q2156822) (← links)
- Valid post-selection inference in model-free linear regression (Q2215767) (← links)
- Bootstrapping and sample splitting for high-dimensional, assumption-lean inference (Q2284380) (← links)
- Two-sample instrumental variable analyses using heterogeneous samples (Q2325638) (← links)
- Double-estimation-friendly inference for high-dimensional misspecified models (Q2684689) (← links)
- Mixed-effect models with trees (Q6106172) (← links)
- Semi-Supervised Linear Regression (Q6110736) (← links)
- Reproducible model selection using bagged posteriors (Q6122016) (← links)
- UNIFORM-IN-SUBMODEL BOUNDS FOR LINEAR REGRESSION IN A MODEL-FREE FRAMEWORK (Q6145543) (← links)
- Consistent and robust inference in hazard probability and odds models with discrete-time survival data (Q6164148) (← links)
- Post-selection inference via algorithmic stability (Q6183754) (← links)
- Higher-Order Least Squares: Assessing Partial Goodness of Fit of Linear Causal Models (Q6567897) (← links)
- A General M-estimation Theory in Semi-Supervised Framework (Q6567902) (← links)
- A Bayesian ``sandwich'' for variance estimation (Q6649133) (← links)
- Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning (Q6651378) (← links)
