hansen.bruce   15

Uniform Convergence Rates for Kernel Estimation with Dependent Data
"This paper presents a set of rate of uniform consistency results for kernel estimators of density functions and regressions functions. We generalize the existing literature by allowing for stationary strong mixing multivariate data with infinite support, and kernels with unbounded support, and general bandwidth sequences. These results are useful for semiparametric estimation based on a first stage nonparametric estimator."
kernel_estimators  mixing  statistical_inference_for_stochastic_processes  statistics  density_estimation  regression  hansen.bruce 
june 2009 by cshalizi
Challenges for Econometric Model Selection
"Standard econometric model selection methods are based on four fundamental errors in approach: parametric vision, the assumption of a true DGP, evaluation based on fit, and ignoring the impact of model uncertainty on inference. Instead, econometric model selection methods should be based on a semiparametric vision, models should be viewed as approximations, models should be evaluated based on their purpose, and model uncertainty should be incorporated into inference methods. These problems have been examined individually, but not jointly, and my view is that future research into econometric model selection should attempt to address all four issues. "
model_selection  econometrics  statistics  nonparametrics  have_read  hansen.bruce 
june 2009 by cshalizi
Interval Forecasts and Parameter Uncertainty
Frequentist prediction interval reflecting parameter uncertainty.
prediction  statistics  in_NB  confidence_sets  to_read  hansen.bruce 
june 2009 by cshalizi
Bruce Hansen's Econometrics Text
"This is a draft of an incomplete first-year Ph.D. econometrics textbook. This manuscript may be printed and reproduced for individual or instructional use, but may not be printed for commercial purposes."
econometrics  statistics  bootstrap  time_series  regression  hansen.bruce 
june 2009 by cshalizi
The Likelihood Ratio Test Under Nonstandard Conditions
I very much like the approach of treating the likelihood ratio as an empirical process; why haven't I seen it before? (Also, the state-of-the-art in simulating Gaussian processes must be much better now than what Hansen was doing in '92, which would make this even more practical.)
empirical_processes  hypothesis_testing  statistics  likelihood_ratio_tests  econometrics  time_series  hansen.bruce  have_read 
june 2009 by cshalizi

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book_reviews  bootstrap  confidence_sets  convergence_of_stochastic_processes  cross-validation  density_estimation  econometrics  empirical_processes  ensemble_methods  ergodic_theory  have_read  hendry.david  hypothesis_testing  in_nb  kernel_estimators  likelihood_ratio_tests  machine_learning  macroeconomics  martingales  method_of_moments  mixing  model_averaging  model_selection  nonparametrics  prediction  racine.jeffrey  re:almost_none  regression  social_science_methodology  statistical_inference_for_stochastic_processes  statistics  time_series  to_read  to_teach:complexity-and-inference  to_teach:data-mining  to_teach:undergrad-ada 

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