修饰语
发表于 2025-3-25 03:58:32
Poverty, Inequality and Development Studies with Machine Learning,iques have been the main contribution in the theoretical arena, whereas taking advantage of the increased availability of new data sources to build or improve the outcome variable has been the main contribution in the empirical front. These inputs would not have been possible without the improvement in computational power.
BLUSH
发表于 2025-3-25 08:11:36
Toward a Concrete Logic: Discretastic discount factor and purposefully to test and evaluate existing asset pricing models. Beyond those pertinent applications, machine learning techniques also lend themselves to prediction problems in the domain of empirical asset pricing.
Diaphragm
发表于 2025-3-25 14:54:19
http://reply.papertrans.cn/31/3015/301474/301474_23.png
确定的事
发表于 2025-3-25 17:04:40
http://reply.papertrans.cn/31/3015/301474/301474_24.png
初学者
发表于 2025-3-25 22:04:03
978-3-031-15151-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
pericardium
发表于 2025-3-26 02:47:02
Econometrics with Machine Learning978-3-031-15149-1Series ISSN 1570-5811 Series E-ISSN 2214-7977
神化怪物
发表于 2025-3-26 07:45:31
http://reply.papertrans.cn/31/3015/301474/301474_27.png
chapel
发表于 2025-3-26 10:00:06
Advanced Studies in Theoretical and Applied Econometricshttp://image.papertrans.cn/e/image/301474.jpg
消毒
发表于 2025-3-26 16:27:54
Martin Groß,Birgit Hennig,Frank Wallhofftric analysis. Specifically, it examines their applicability in the context of linear regression models. The asymptotic properties of these estimators are discussed and the implications on statistical inference are explored. Given the existing knowledge of these estimators, the chapter advocates the
吃掉
发表于 2025-3-26 17:35:53
http://reply.papertrans.cn/31/3015/301474/301474_30.png