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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محفوظ في:

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Arsua, Andre Millard M, Azucena, Raphael Matthew D
التنسيق:	text
اللغة:	English
منشور في:	Animo Repository 2022
الموضوعات:	Gross domestic product > Philippines Forecasting Mathematics
الوصول للمادة أونلاين:	https://animorepository.dlsu.edu.ph/etdb_math/3 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1003&context=etdb_math
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!

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