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Forecasting State Tax Revenues, Recessions and Their Uncertainties Using Mixed-Frequency Data, Model Averaging, Bootstrap, ROC Analysis and Machine Learning
Forecasting State Tax Revenues, Recessions and Their Uncertainties Using Mixed-Frequency Data, Model Averaging, Bootstrap, ROC Analysis and Machine Learning
- 자료유형
- 학위논문
- Control Number
- 0015760246
- International Standard Book Number
- 9798664751994
- Dewey Decimal Classification Number
- 350
- Main Entry-Personal Name
- Yang, Cheng.
- Publication, Distribution, etc. (Imprint
- [Sl] : State University of New York at Albany, 2020
- Publication, Distribution, etc. (Imprint
- Ann Arbor : ProQuest Dissertations & Theses, 2020
- Physical Description
- 162 p
- General Note
- Source: Dissertations Abstracts International, Volume: 82-03, Section: B.
- General Note
- Advisor: Lahiri, Kajal.
- Dissertation Note
- Thesis (Ph.D.)--State University of New York at Albany, 2020.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Subject Added Entry-Topical Term
- Public administration
- Subject Added Entry-Topical Term
- Artificial intelligence
- Subject Added Entry-Topical Term
- COVID-19
- Index Term-Uncontrolled
- Forecasting
- Index Term-Uncontrolled
- Recession
- Index Term-Uncontrolled
- Tax revenues
- Added Entry-Corporate Name
- State University of New York at Albany Economics
- Host Item Entry
- Dissertations Abstracts International. 82-03B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:591609
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