Forecasting the Philippines’ GDP growth using long short-term memory neural network regression and mixed-data sampling regression models

Forecasting the Philippines’ GDP growth using long short-term memory neural network regression and mixed-data sampling regression models

Having better forecasts is crucial in the Philippines’ state of economic recovery. The study intends to forecast the Philippines’ GDP growth rate from 2011 to 2021 using two emerging methods used for mixed-frequency data: Mixed-Data Sampling (MIDAS) Regression and Long Short-Term Memory (LSTM) Neura...

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書目詳細資料
Main Authors:	Arsua, Andre Millard M, Azucena, Raphael Matthew D
格式:	text
語言:	English
出版:	Animo Repository 2022
主題:	Gross domestic product > Philippines Forecasting Mathematics
在線閱讀:	https://animorepository.dlsu.edu.ph/etdb_math/3 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1003&context=etdb_math
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