Titlebook: Data Science for Financial Econometrics; Nguyen Ngoc Thach,Vladik Kreinovich,Nguyen Duc Tru Book 2021 The Editor(s) (if applicable) and Th

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Mohamed Hafez,Koji Morinishi,Jacques Periaux previous researches in other countries. Survey data was collected from 1538 respondents living in HCM City, Vietnam. The research model was proposed from the studies of University Reputation. The reliability and validity of the scale were evaluated by Cronbach‘s Alpha, Average Variance Extracted (P

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W. Haase,V. Maigret,M. Stettneresian normal linear regression against the least-square regression based on the frequentist approach, the results of this study demonstrate that cultural values have strong effects on economic development in the studied countries. Power distance and uncertainty avoidance indices are negatively corre

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Alain Lerat,Christophe Corre,Grégoire Hanssfor period 2006–2017. The finding shows that the interest rate pass-through from policy rate to interbank rate and from interbank rate to market rates are not perfect. Particularly, the effect of interbank rate on deposit and lending rates is weak, not as high as SBV’s expectation. The speed of inte

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On Latent Fingerprint Image Qualityhelps budget planning process take a more proactive approach. Like many other economic variables such as oil prices, stock prices, interest rates, etc., public investment can also be forecasted by different quantitative methods. In this paper, we apply the Ordinary Least Square (OLS), Ridge, and Las

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https://doi.org/10.1007/978-3-030-48853-6Computational Intelligence; Intelligent Systems; Econometrics; Data Science; Probabilistic Methods; Econo

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978-3-030-48855-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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A Theory-Based Lasso for Time-Series Datatheory-based or ‘rigorous’ lasso of Bickel et al. (.), Belloni et al. (.), Belloni and Chernozhukov (.), Belloni et al. (.) and recently extended to the case of dependent data by Chernozhukov et al. (.), where the lasso penalty level is derived on theoretical grounds. The rigorous lasso has appealin

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Why LASSO, EN, and CLOT: Invariance-Based Explanationsed. In such situations, a reasonable idea is to take into account that the values of the corresponding parameters should not be too large; this idea is known as regularization. Several different regularization techniques have been proposed; empirically the most successful are LASSO method, when we

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