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  • Search: subject:"Multiple data sets"
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Subject
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Multiple data sets 4 Missing data 2 Scale 2 Asymptotic normality 1 Australia 1 Bifurcating autoregressive model 1 Canonical correlation analysis 1 Causal Inference 1 Causality analysis 1 Cell division data 1 Discrete choice models 1 Estimation theory 1 Factor analysis 1 Faktorenanalyse 1 Fatigue 1 Federated Learning 1 Generalized mixed logit 1 Induktive Statistik 1 Kausalanalyse 1 Large and 1 Latent class 1 Learning 1 Learning process 1 Least-squares estimation 1 Lernprozess 1 MNL 1 Mixed logit 1 Multiple Data Sets 1 Multiple data sets estimation 1 New Zealand 1 Nonsingular transformation 1 Panel 1 Panel study 1 Principal component analysis 1 Principal components 1 Procrustes analysis 1 Propensity Scores 1 Replicated trees 1 Scale MNL 1 Schätztheorie 1
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Undetermined 5 Free 1
Type of publication
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Article 5 Book / Working Paper 1
Type of publication (narrower categories)
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Arbeitspapier 1 Article in journal 1 Aufsatz in Zeitschrift 1 Graue Literatur 1 Non-commercial literature 1 Working Paper 1
Language
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Undetermined 4 English 2
Author
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Xiong, Ruoxuan 2 Adachi, Kohei 1 Athey, Susan 1 Daly, Andrew 1 Duan, Junting 1 Gégout-Petit, Anne 1 Hensher, David 1 Hensher, David A. 1 Hess, Stephane 1 Koenecke, Allison 1 Li, Zheng 1 Marsalle, Laurence 1 Pelger, Markus 1 Powell, Michael 1 Rose, John 1 Shen, Zhu 1 Vogelstein, Joshua T. 1 de Saporta, Benoîte 1
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Published in...
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Computational Statistics 1 Computational Statistics & Data Analysis 1 Journal of econometrics 1 Stanford University Graduate School of Business Research Paper 1 Transportation 1 Transportation Research Part A: Policy and Practice 1
Source
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RePEc 4 ECONIS (ZBW) 2
Showing 1 - 6 of 6
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Federated Causal Inference in Heterogeneous Observational Data
Xiong, Ruoxuan; Koenecke, Allison; Powell, Michael; … - 2023
Analyzing observational data from multiple sources can be useful for increasing statistical power to detect a treatment effect; however, practical constraints such as privacy considerations may restrict individual-level information sharing across data sets. This paper develops federated methods...
Persistent link: https://www.econbiz.de/10014087886
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Target PCA: transfer learning large dimensional panel data
Duan, Junting; Pelger, Markus; Xiong, Ruoxuan - In: Journal of econometrics 244 (2024) 2, pp. 1-28
Persistent link: https://www.econbiz.de/10015553735
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Statistical study of asymmetry in cell lineage data
de Saporta, Benoîte; Gégout-Petit, Anne; Marsalle, … - In: Computational Statistics & Data Analysis 69 (2014) C, pp. 15-39
A rigorous methodology is proposed to study cell division data consisting in several observed genealogical trees of possibly different shapes. The procedure takes into account missing observations, data from different trees, as well as the dependence structure within genealogical trees. Its main...
Persistent link: https://www.econbiz.de/10010709955
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Generalized joint Procrustes analysis
Adachi, Kohei - In: Computational Statistics 28 (2013) 6, pp. 2449-2464
for multiple data sets of the same size. The transformation is made so that multiple score and loading matrices are …
Persistent link: https://www.econbiz.de/10010998509
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Does the choice model method and/or the data matter?
Hensher, David; Rose, John; Li, Zheng - In: Transportation 39 (2012) 2, pp. 351-385
Persistent link: https://www.econbiz.de/10010867520
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Not bored yet – Revisiting respondent fatigue in stated choice experiments
Hess, Stephane; Hensher, David A.; Daly, Andrew - In: Transportation Research Part A: Policy and Practice 46 (2012) 3, pp. 626-644
Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same...
Persistent link: https://www.econbiz.de/10010576630
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