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type_genre:"Arbeitspapier"
type_genre:"Bibliographie enthalten"
~isPartOf:"Beiträge aus dem Institut für Statistik und Ökonometrie der Universität Hamburg"
~isPartOf:"Working paper / Department of Econometrics and Business Statistics, Monash University"
~source:"econis"
~subject:"Regressionsanalyse"
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Search: subject_exact:"Estimation theory"
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Regressionsanalyse
Estimation theory
193
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Gao, Jiti
16
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Knautz, Henning
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King, Maxwell L.
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Tjostheim, Dag
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Yin, Jiying
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Beiträge aus dem Institut für Statistik und Ökonometrie der Universität Hamburg
Working paper / Department of Econometrics and Business Statistics, Monash University
CEMMAP working papers / Centre for Microdata Methods and Practice
97
Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund
72
Discussion paper series / IZA
42
Discussion papers of interdisciplinary research project 373
40
Cowles Foundation discussion paper
39
Discussion paper / Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München
32
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31
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24
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23
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20
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18
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Department of Economics working paper series / McMaster University, Department of Economics
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Discussion paper / University of Bristol, Department of Economics
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Discussion papers / Courant Research Centre "Poverty, Equity and Growth in Developing and Transition Countries: Statistical Methods and Empirical Analysis"
6
Discussion papers / Graduate School of Economics, Hitotsubashi University
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Working paper / Iowa State University, Department of Economics
6
Working paper series / University of Zurich, Department of Economics
6
Working papers
6
Working papers / Penn Institute for Economic Research
6
CAEPR working papers
5
CEMFI working paper
5
Discussion papers in economics / Center for Economic Analysis, Department of Economics, University of Colorado at Boulder : Working paper
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1
A localised neural network with dependent data: estimation and inference
Gao, Jiti
;
Peng, Bin
;
Yang, Yanrong
-
2023
Persistent link: https://www.econbiz.de/10014452592
Saved in:
2
Estimation of semiparametric multi- index models using deep neural networks
Donga, Chaohua
;
Gao, Jiti
;
Peng, Bin
;
Yan, Yayi
-
2023
Persistent link: https://www.econbiz.de/10014452599
Saved in:
3
Multi-level panel data models : estimation and empirical analysis
Feng, Guohua
;
Gao, Jiti
;
Peng, Bin
-
2022
Persistent link: https://www.econbiz.de/10013193952
Saved in:
4
Semiparametric single-index predictive regression
Zhou, Weilun
;
Gao, Jiti
;
Harris, David
;
Kew, Hsein
-
2019
Persistent link: https://www.econbiz.de/10012606715
Saved in:
5
Fast forecast reconciliation using linear models
Ashouri, Mahsa
;
Hyndman, Rob J.
;
Shmueli, Galit
-
2019
Persistent link: https://www.econbiz.de/10012606728
Saved in:
6
Nonparametric kernel estimation of the impact of tax policy on the demand for private health insurance in Australia
Gong, Xiaodong
;
Gao, Jiti
-
2017
Persistent link: https://www.econbiz.de/10011782017
Saved in:
7
Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction
Cheng, Tingting
;
Gao, Jiti
;
Linton, Oliver
-
2017
Persistent link: https://www.econbiz.de/10011782226
Saved in:
8
Bayesian indirect inference and the ABC of GMM
Creel, Michael D.
;
Gao, Jiti
;
Hong, Han
;
Kristensen, Dennis
-
2016
Persistent link: https://www.econbiz.de/10011781486
Saved in:
9
Error-in-variables jump regression using local clustering
Kang, Yicheng
;
Gong, Xiaodong
;
Gao, Jiti
;
Qiu, Peihua
-
2016
Persistent link: https://www.econbiz.de/10011781755
Saved in:
10
Specification testing for nonlinear multivariate cointegrating regressions
Dong, Chaohua
;
Gao, Jiti
;
Tjostheim, Dag
;
Yin, Jiying
-
2016
-
Revised 14, 08
Persistent link: https://www.econbiz.de/10011781762
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