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  • Search: subject:"non-asymptotic bound"
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Year of publication
Subject
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Many moment inequalities 6 moderate deviation 5 multiplier and empirical bootstrap 5 non-asymptotic bound 5 self-normalized sum 5 Bootstrap approach 4 Bootstrap-Verfahren 4 Multiplier 3 Multiplikator 3 Statistical test 3 Statistischer Test 3 Estimation theory 2 Forecast Combination 2 Method of moments 2 Momentenmethode 2 Multiplicative Update 2 Non-asymptotic Bound 2 On-line Learning 2 Schätztheorie 2 Theorie 2 Theory 2 Discrete choice 1 Diskrete Entscheidung 1 Econometrics 1 Estimation 1 Expert 1 Market structure 1 Marktstruktur 1 Model Selection 1 Moderate deviation 1 Multiplier and empirical bootstrap 1 Non-asymptotic bound 1 Regression analysis 1 Regressionsanalyse 1 Schätzung 1 Self-normalized sum 1 Shifting 1 Ökonometrie 1
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Online availability
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Free 7 Undetermined 1
Type of publication
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Book / Working Paper 7 Article 1
Type of publication (narrower categories)
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Working Paper 5 Arbeitspapier 3 Graue Literatur 3 Non-commercial literature 3 Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 8
Author
All
Chernozhukov, Victor 5 Chetverikov, Denis 5 Kato, Kengo 5 Sancetta, A. 2 Četverikov, Denis N. 1
Institution
All
Faculty of Economics, University of Cambridge 2
Published in...
All
CEMMAP working papers / Centre for Microdata Methods and Practice 3 Cambridge Working Papers in Economics 2 cemmap working paper 2 The review of economic studies : RES 1
Source
All
ECONIS (ZBW) 4 EconStor 2 RePEc 2
Showing 1 - 8 of 8
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Testing many moment inequalities
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2016
This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are variety of economic applications where the problem of testing many moment in- equalities appears; a notable...
Persistent link: https://www.econbiz.de/10011594352
Saved in:
Cover Image
Testing many moment inequalities
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2016 - This version: September 10, 2015
This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are variety of economic applications where the problem of testing many moment in- equalities appears; a notable...
Persistent link: https://www.econbiz.de/10011525823
Saved in:
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Inference on causal and structural parameters using many moment inequalities
Chernozhukov, Victor; Četverikov, Denis N.; Kato, Kengo - In: The review of economic studies : RES 86 (2019) 5, pp. 1867-1900
Persistent link: https://www.econbiz.de/10012111907
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Cover Image
Testing many moment inequalities
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2014
This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are a variety of economic applications where the problem of testing many moment in- equalities appears; a notable...
Persistent link: https://www.econbiz.de/10011445706
Saved in:
Cover Image
Testing many moment inequalities
Chernozhukov, Victor; Chetverikov, Denis; Kato, Kengo - 2014 - This version: December 16, 2014
This paper considers the problem of testing many moment inequalities where the number of moment inequalities, denoted by p, is possibly much larger than the sample size n. There are a variety of economic applications where the problem of testing many moment in- equalities appears; a notable...
Persistent link: https://www.econbiz.de/10010459258
Saved in:
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Testing regression monotonicity in econometric models
Chetverikov, Denis - 2012
Monotonicity is a key qualitative prediction of a wide array of economic models derived via robust comparative statics. It is therefore important to design effective and practical econometric methods for testing this prediction in empirical analysis. This paper develops a general nonparametric...
Persistent link: https://www.econbiz.de/10009667989
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Online Forecast Combination for Dependent Heterogeneous Data
Sancetta, A. - Faculty of Economics, University of Cambridge - 2007
This paper studies a procedure to combine individual forecasts that achieve theoretical optimal performance. The results apply to a wide variety of loss functions and no conditions are imposed on the data sequences and the individual forecasts apart from a tail condition. The theoretical results...
Persistent link: https://www.econbiz.de/10005783740
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Forecasting Distributions with Experts Advice
Sancetta, A. - Faculty of Economics, University of Cambridge - 2005
This paper considers forecasts of the distribution of data whose distribution function is possibly time varying. The forecast is achieved via time varying combinations of experts’ forecasts. We derive theoretical worse case bounds for general algorithms based on multiplicative updates of the...
Persistent link: https://www.econbiz.de/10005783716
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