MODEL SELECTION AND INFERENCE: FACTS AND FICTION
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Publication:5697622
DOI10.1017/S0266466605050036zbMath1085.62004OpenAlexW2022943305MaRDI QIDQ5697622
Benedikt M. Pötscher, Hannes Leeb
Publication date: 18 October 2005
Published in: Econometric Theory (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1017/s0266466605050036
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Cites Work
- Asymptotic properties of maximum likelihood estimators based on conditional specification
- Asymptotic properties of criteria for selection of variables in multiple regression
- Order estimation in ARMA-models by Lagrangian multiplier tests
- On preliminary test and shrinkage M-estimation in linear models
- Strong rules for detecting the number of breaks in a time series
- Asymptotics for Lasso-type estimators.
- Consistent order selection with strongly dependent data and its application to efficient estimation.
- Consistent covariate selection and post model selection inference in semiparametric regression.
- On the harm that ignoring pretesting can cause
- Admissible variable-selection procedures when fitting regression models by least squares for prediction
- Complete Consistency: A Testing Analogue of Estimator Consistency
- Model selection by multiple test procedures
- The effect of order estimation on estimating the peak frequency of an autoregressive spectral density
- On model structure testing in system identification
- A bootstrap theorem for a preliminary test estimator
- Atomic Decomposition by Basis Pursuit
- Accounting for Lag Order Uncertainty in Autoregressions: the Endogenous Lag Order Bootstrap Algorithm
- The distribution of estimators after model selection:large and small sample results
- A Consistent Method for the Selection of Relevant Instruments
- Bounds for inference with nuisance parameters present only under the alternative
- THE CHOICE BETWEEN SETS OF REGRESSORS
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Frequentist Model Average Estimators
- Least squares, preliminary test and Stein‐type estimation in general vector AR(p) models
- A Statistical View of Some Chemometrics Regression Tools
- Lower Risk Bounds and Properties of Confidence Sets for Ill-Posed Estimation Problems with Applications to Spectral Density and Persistence Estimation, Unit Roots, and Estimation of Long Memory Parameters
- Non-Optimality of Preliminary-Test Estimators for the Mean of a Multivariate Normal Distribution
- Incorporating lag order selection uncertainty in parameter inference for AR models