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Items where Subject is "C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C55 - Large Data Sets: Modeling and Analysis"

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Number of items at this level: 37.

English

Asante Gyamerah, Samuel and Ngare, Philip and Ikpe, Dennis (2018): A Levy Regime-Switching Temperature Dynamics Model for Weather Derivatives. Published in: International Journal of Stochastic Analysis , Vol. 2018, No. 8534131 (10 June 2018): pp. 1-16.

Bakshi, Sanjeev and Pathak, Prasanta (2009): Health at Old Ages in India: Statistical Exposition of Its Socio-Cultural and Gender Dimensions.

Ben Jebli, Mehdi (2015): The Impact of Combustible Renewables and Waste Consumption and Transport on the Environmental Degradation: The Case of Tunisia.

Berg, Tim Oliver (2015): Multivariate Forecasting with BVARs and DSGE Models.

Bonga-Bonga, Lumengo and Mabe, Queen Magadi (2016): How financially integrated are trading blocs in Africa?

Braaksma, Barteld and Zeelenberg, Kees (2015): “Re-make/Re-model”: Should big data change the modelling paradigm in official statistics? Published in: Statistical Journal of the IAOS , Vol. 31, No. 2 (2015): pp. 193-202.

Byambasuren, Tsenguunjav and Gochoo, Munkh-Erdene (2015): Optimizing the Structure of Mongolian Foreign Trade and the Alternative Policy of Successful Transition.

Carbajal De Nova, Carolina (2014): Synthetic data: an endogeneity simulation.

Chakraborty, Lekha S and Singh, Yadawendra (2018): Fiscal Policy, as the “Employer of Last Resort”: Impact of Direct fiscal transfer (MGNREGA) on Labour Force Participation Rates in India.

Chu, Ba (2017): Composite Quasi-Likelihood Estimation of Dynamic Panels with Group-Specific Heterogeneity and Spatially Dependent Errors.

Cordero, José Manuel and Cristobal, Victor and Santín, Daniel (2017): Causal Inference on Education Policies: A Survey of Empirical Studies Using PISA, TIMSS and PIRLS.

Cordero, José Manuel and Gil, María and Pedraja Chaparro, Francisco (2016): Exploring the effect of financial literacy courses on student achievement: a cross-country approach using PISA 2012 data.

Einian, Majid and Nili, Masoud (2016): Consumption Smoothing and Borrowing Constraints: Evidence from Household Surveys of Iran.

Gangopadhyay, Kausik and Jangir, Abhishek and Sensarma, Rudra (2015): Forecasting the price of gold: An error correction approach. Published in: IIMB Management Review , Vol. 28, No. 1 (2016): pp. 6-12.

Genge, Ewa and Bartolucci, Francesco (2019): Are attitudes towards immigration changing in Europe? An analysis based on bidimensional latent class IRT models.

Gerunov, Anton (2014): Big Data Approaches to Modeling the Labor Market. Published in: Proceedings of the International Conference on Big Data, Knowledge and Control Systems Engineering, 2014 (2014): pp. 47-56.

Hännikäinen, Jari (2016): When does the yield curve contain predictive power? Evidence from a data-rich environment.

Indaco, Agustín (2019): From Twitter to GDP: Estimating Economic Activity From Social Media.

Kim, Hyeongwoo and Ko, Kyunghwan (2018): Improving Forecast Accuracy of Financial Vulnerability: PLS Factor Model Approach.

Loermann, Julius and Maas, Benedikt (2019): Nowcasting US GDP with artificial neural networks.

Maas, Benedikt (2019): Short-term forecasting of the US unemployment rate.

Mitrofanova, Ekaterina S. and Artamonova, Alyona V. (2016): Studying Family Formation Trajectories’ Deinstitutionalization in Russia Using Sequence Analysis. Published in: CEUR Workshop Proceeding , Vol. 1627, No. Experimental Economics and Machine Learning (25 July 2016): pp. 34-47.

Nikitinsky, Nikita and Shashev, Sergey and Kachurina, Polina and Bespalov, Aleksander (2016): Big Data and Machine Learning in Government Projects: Expert Evaluation Case. Published in: CEUR Workshop Proceeding , Vol. 1627, No. Experimental Economics and Machine Learning (25 July 2016)

Ogunlesi, Ayodeji (2018): Agricultural Productivity, Fiscal and Trade Policies Nexus in Sub-Saharan Africa: A Panel Structural Vector Error Correction Model Analysis.

Pallara, Kevin (2016): The dynamic effects of government spending: a FAVAR approach.

Ramadas, Sendhil and Palanisamy, Ramasundaram and Kuruvila, Anil and Chandrasekaran, Sundaramoorthy and Singh, Randhir and Sharma, Indu (2014): Food Price Volatility in India – Drivers, Impact and Policy Response.

Situngkir, Hokky (2015): Indonesia embraces the Data Science. Published in: SEAMS 7th Conference, Jogjakarta, Indonesia

Tagiew, Rustam and Ignatov, Dmitry I. (2017): Behavior Mining in h-index Ranking Game. Published in: CEUR Workshop Proceeding , Vol. 1968, No. Experimental Economics and Machine Learning (28 October 2017): pp. 52-61.

Tierney, Heather L.R. and Kim, Jiyoon (June) and Nazarov, Zafar (2018): The Effects of Temporal Aggregation on Search Engine Data.

Verstappen, Ksenia (2018): Economics of big data: review of best papers for January 2018.

Xu, Ning and Hong, Jian and Fisher, Timothy (2016): Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression.

Xu, Ning and Hong, Jian and Fisher, Timothy (2016): Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso.

Yang, Bill Huajian (2019): Monotonic Estimation for Probability Distribution and Multivariate Risk Scales by Constrained Minimum Generalized Cross-Entropy. Forthcoming in: International Journal of Machine Learning and Computing

Yang, Bill Huajian (2019): Monotonic Estimation for the Survival Probability over a Risk-Rated Portfolio by Discrete-Time Hazard Rate Models. Forthcoming in: International Journal of Machine Learning and Computing

bailek, Alexandra (2018): Economic Impact Analysis of Hospital Readmission Rate and Service Quality Using Machine Learning. Published in:

French

Albert, Pierre and Ghassan, Hassan B. and Huiban, Jean Pierre and Martin, Michel (1992): L'Industrie Laitière Française: Modèles d'Entreprises et Formes de Concurrence/Coordination Inter-Firmes.

Trabelsi, Mohamed Ali (2016): Analyse des données : Résumé de cours avec exercices d’application. Published in: Editions Universitaires Européennes No. ISBN: 978-3-639-52294-5 (2016): pp. 1-43.

This list was generated on Sun Sep 15 14:15:27 2019 CEST.
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