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subject:"Monte-Carlo-Simulation"
subject:"Panel study"
~isPartOf:"Working paper / Department of Econometrics and Business Statistics, Monash University"
~person:"Gao, Jiti"
~subject:"Nichtlineare Regression"
~subject:"Regression analysis"
~type:"book"
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Monte-Carlo-Simulation
Panel study
Nichtlineare Regression
Regression analysis
Estimation theory
62
Schätztheorie
62
Nichtparametrisches Verfahren
29
Nonparametric statistics
29
Time series analysis
29
Zeitreihenanalyse
29
Estimation
19
Schätzung
19
Panel
16
Regressionsanalyse
16
Cointegration
8
Kointegration
8
Asymptotic theory
4
Bayes-Statistik
4
Bayesian inference
4
Forecasting model
4
Prognoseverfahren
4
Statistical test
4
Statistischer Test
4
Börsenkurs
3
Capital income
3
Cross-sectional dependence
3
Demand
3
Demand for private health insurance
3
Factor analysis
3
Faktorenanalyse
3
Hierarchical Model
3
Kapitaleinkommen
3
Maximum likelihood estimation
3
Maximum-Likelihood-Schätzung
3
Method of moments
3
Momentenmethode
3
Nachfrage
3
Nonlinear regression
3
Nonparametric Kernel Estimation
3
Private Krankenversicherung
3
Private health insurance
3
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32
Graue Literatur
32
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32
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32
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32
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Gao, Jiti
Peng, Bin
9
Yang, Yanrong
8
Gong, Xiaodong
5
Hyndman, Rob J.
5
Zhang, Xibin
5
Liu, Fei
4
Sarafidis, Vasilis
4
Cheng, Tingting
3
Dong, Chaohua
3
Feng, Guohua
3
Hong, Han
3
Jiang, Bin
3
King, Maxwell L.
3
Martin, Gael M.
3
Pan, Guangming
3
Athanasopoulos, George
2
Dokumentov, Alexander
2
Frazier, David T.
2
Liang, Xuan
2
Linton, Oliver
2
Robert, Christian P.
2
Shang, Han Lin
2
Tjostheim, Dag
2
Vahid, Farshid
2
Yan, Yayi
2
Yin, Jiying
2
Ashouri, Mahsa
1
Bai, Yu
1
Cai, Biqing
1
Chen, Haotian
1
Chen, Jia
1
Creel, Michael D.
1
Cui, Guowei
1
Donga, Chaohua
1
Forbes, Catherine Scipione
1
Forchini, Giovanni
1
Guo, Meihui
1
Harris, David
1
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Working paper / Department of Econometrics and Business Statistics, Monash University
Cowles Foundation Discussion Paper
3
Cowles Foundation discussion paper
2
CEMMAP working papers / Centre for Microdata Methods and Practice
1
Cambridge working papers in economics
1
Cambridge-INET working papers
1
Contributions to statistics
1
Discussion paper series / IZA
1
School of Accounting, Finance and Economics & FEMARC working paper series
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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
Estimation and inference for three-dimensional panel data models
Feng, Guohua
;
Gao, Jiti
;
Liu, Fei
;
Peng, Bin
-
2023
Persistent link: https://www.econbiz.de/10014452624
Saved in:
4
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:
5
Semiparametric spatial autoregressive panel data model with fixed effects and time-varying coefficients
Liang, Xuan
;
Gao, Jiti
;
Gong, Xiaodong
-
2021
Persistent link: https://www.econbiz.de/10012614543
Saved in:
6
Time-varying panel data models with an additive factor structure
Liu, Fei
;
Gao, Jiti
;
Yang, Yanrong
-
2020
Persistent link: https://www.econbiz.de/10012610885
Saved in:
7
Binary response models for heterogeneous panel data with interactive fixed effects
Gao, Jiti
;
Liu, Fei
;
Peng, Bin
-
2020
Persistent link: https://www.econbiz.de/10012610898
Saved in:
8
A varying-coefficient panel data model with fixed effects : theory and an application to U.S. commercial banks
Feng, Guohua
;
Gao, Jiti
;
Peng, Bin
;
Zhang, Xiaohui
-
2015
Persistent link: https://www.econbiz.de/10011781225
Saved in:
9
Nonparametric estimation in panel data models with heterogeneity and time-varyingness
Liu, Fei
;
Gao, Jiti
;
Yang, Yanrong
-
2019
Persistent link: https://www.econbiz.de/10012606705
Saved in:
10
Semiparametric single-index predictive regression
Zhou, Weilun
;
Gao, Jiti
;
Harris, David
;
Kew, Hsein
-
2019
Persistent link: https://www.econbiz.de/10012606715
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