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Search: subject:"least squares method"
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Least squares method
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Ringle, Christian M.
83
Sarstedt, Marko
56
Hair, Joseph F.
35
Henseler, Jörg
19
Wagner, Martin
16
Nielsen, Bent
13
Perron, Pierre
13
Phillips, Peter C. B.
12
Rose, Andrew
11
Wolf, Michael
11
Cheah, Jun-Hwa
10
Winkelmann, Rainer
10
Bask, Mikael
9
Becker, Jan-Michael
9
Hansen, Bruce E.
9
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9
Kiviet, J. F.
9
Nitzl, Christian
9
Stentoft, Lars
9
Słoczyński, Tymon
9
Baltagi, Badi H.
8
Gao, Jiti
8
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8
Kapetanios, George
8
Kim, Hyeongwoo
8
Mihov, Ilian
8
Romano, Joseph P.
8
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7
Berenguer-Rico, Vanessa
7
Denteh, Augustine
7
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7
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7
Lesage, James P.
7
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7
Nguimkeu, Pierre
7
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7
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7
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European University Institute / Department of Economics
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Nuffield College
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Elinkeinoelämän Tutkimuslaitos
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Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues - GEWISOLA
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International Conference on Partial Least Squares Structural Equation Modeling Conference <2022, Cluj-Napoca; Online>
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Queen Mary College / Department of Economics
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Springer Fachmedien Wiesbaden
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Technical report / Sonderforschungsbereich 475 Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund
14
Discussion paper / Centre for Economic Policy Research
13
Oxford bulletin of economics and statistics
13
European journal of operational research : EJOR
12
Handbook of partial least squares : concepts, methods and applications
12
International Journal of Energy Economics and Policy : IJEEP
12
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10
European journal of marketing
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Empirical economics : a journal of the Institute for Advanced Studies, Vienna, Austria
9
Organizational research methods : ORM
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Applied economics letters
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ECONIS (ZBW)
2,306
RePEc
105
USB Cologne (EcoSocSci)
6
EconStor
4
BASE
2
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2
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511
Two-stage least squares random forests with an application to Angrist and Evans (1998)
Biewen, Martin
;
Kugler, Philipp
- In:
Economics letters
204
(
2021
),
pp. 1-5
Persistent link: https://www.econbiz.de/10012607793
Saved in:
512
Deep learning-based least squares forward-backward stochastic differential equation solver for high-dimensional derivative pricing
Liang, Jian
;
Xu, Zhe
;
Li, Peter
- In:
Quantitative finance
21
(
2021
)
8
,
pp. 1309-1323
Persistent link: https://www.econbiz.de/10012608649
Saved in:
513
Asset shortages and economic operating system based on two-stage least-squares regression
Yang, Yang
;
Liu, Shuwen
- In:
International journal of shipping and transport …
13
(
2021
)
5
,
pp. 466-483
Persistent link: https://www.econbiz.de/10012613749
Saved in:
514
Estimating multiple breaks in nonstationary autoregressive models
Pang, Tianxiao
;
Du, Lingjie
;
Chong, Terence Tai-Leung
- In:
Journal of econometrics
221
(
2021
)
1
,
pp. 277-311
Persistent link: https://www.econbiz.de/10012618836
Saved in:
515
Complete subset least squares support vector regression
Qiu, Yue
- In:
Economics letters
200
(
2021
),
pp. 1-5
Persistent link: https://www.econbiz.de/10012606827
Saved in:
516
Panel threshold spatial Durbin models with individual fixed effects
Wei, Lili
;
Zhang, Chunli
;
Su, Jen-je
;
Yang, Lixiong
- In:
Economics letters
201
(
2021
),
pp. 1-4
Persistent link: https://www.econbiz.de/10012606957
Saved in:
517
Sampling weight adjustments in partial least squares structural equation modeling : guidelines and illustrations
Cheah, Jun-Hwa
;
Roldán, José L.
;
Ciavolino, Enrico
; …
- In:
Total quality management & business excellence
32
(
2021
)
14
,
pp. 1594-1613
Persistent link: https://www.econbiz.de/10012649852
Saved in:
518
The causal interpretation of two-stage least squares with multiple instrumental variables
Mogstad, Magne
;
Torgovitsky, Alexander
;
Walters, …
- In:
American economic review
111
(
2021
)
11
,
pp. 3663-3698
Persistent link: https://www.econbiz.de/10012656025
Saved in:
519
Portfolio efficiency with high-dimensional data as conditioning information
Vigo, Caio
- In:
International review of financial analysis
77
(
2021
),
pp. 1-23
Persistent link: https://www.econbiz.de/10012806338
Saved in:
520
Partial Least Square Structural Equation Modelling (PLS-SEM) in marketing research
Rughoobur-Seetah, Soujata
;
Nunkoo, Robin
; …
- In:
Handbook of research methods for marketing management
,
(pp. 171-191)
.
2021
Persistent link: https://www.econbiz.de/10013171789
Saved in:
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