Parametric or nonparametric? A parametricness index for model selection
From MaRDI portal
Publication:651025
DOI10.1214/11-AOS899zbMath1227.62055arXiv1202.0391OpenAlexW3102531650MaRDI QIDQ651025
Publication date: 8 December 2011
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1202.0391
Asymptotic properties of parametric estimators (62F12) Linear regression; mixed models (62J05) General nonlinear regression (62J02) Diagnostics, and linear inference and regression (62J20)
Related Items
On improvability of model selection by model averaging, Simultaneous confidence bands for sequential autoregressive fitting, Optimal Integrating Learning for Split Questionnaire Design Type Data, Unnamed Item, Parametric or nonparametric? A parametricness index for model selection, On model selection from a finite family of possibly misspecified time series models, Cross-validation for selecting a model selection procedure, Non-monotonic penalizing for the number of structural breaks, Multi-model inference of non-random mating from an information theoretic approach, Variable selection In regression models using global sensitivity analysis
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A unified approach to model selection and sparse recovery using regularized least squares
- The Adaptive Lasso and Its Oracle Properties
- Fisher lecture: Dimension reduction in regression
- Parametric or nonparametric? A parametricness index for model selection
- Asymptotic properties of criteria for selection of variables in multiple regression
- Can one estimate the conditional distribution of post-model-selection estimators?
- The sparsity and bias of the LASSO selection in high-dimensional linear regression
- Evaluation and selection of models for out-of-sample prediction when the sample size is small relative to the complexity of the data-generating process
- Hedonic housing prices and the demand for clean air
- Estimating the dimension of a model
- Risk bounds for model selection via penalization
- Approximation and estimation bounds for artificial neural networks
- Heuristics of instability and stabilization in model selection
- Some issues in the foundation of statistics. (With comments by J. Berger, E. L. Lehmann, P. W. Holland, C. C. Clogg, N. W. Henry and the author's rejoinder)
- Information-theoretic determination of minimax rates of convergence
- Combining different procedures for adaptive regression
- Density estimation by wavelet thresholding
- Optimal global rates of convergence for nonparametric regression
- Least angle regression. (With discussion)
- On estimating a density using Hellinger distance and some other strange facts
- Order selection for same-realization predictions in autoregressive processes
- Local Rademacher complexities and oracle inequalities in risk minimization. (2004 IMS Medallion Lecture). (With discussions and rejoinder)
- On the harm that ignoring pretesting can cause
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Consistency of cross validation for comparing regression procedures
- Model selection via testing: an alternative to (penalized) maximum likelihood estimators.
- High-dimensional graphs and variable selection with the Lasso
- Fitting autoregressive models for prediction
- Accumulated prediction errors, information criteria and optimal forecasting for autoregressive time series
- Calibration and empirical Bayes variable selection
- Model selection for regression on a random design
- Approximate efficiency of a selection procedure for the number of regression variables
- Model Selection and Model Averaging
- Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation
- Nonparametric Estimation of a Density of Unknown Smoothness
- Estimating Optimal Transformations for Multiple Regression and Correlation
- A strongly consistent procedure for model selection in a regression problem
- An optimal selection of regression variables
- Minimum complexity density estimation
- Inference after variable selection in linear regression models
- An asymptotic property of model selection criteria
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Adaptive Model Selection
- The Focused Information Criterion
- ON VARIABLE SELECTION IN LINEAR REGRESSION
- Aggregation and Sparsity Via ℓ1 Penalized Least Squares
- Tuning parameter selectors for the smoothly clipped absolute deviation method
- Some Comments on C P
- Optimal Model Assessment, Selection, and Combination
- On the Large-Sample Minimal Coverage Probability of Confidence Intervals After Model Selection
