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A third-order autoregressive model is fitted to an annual time series with 16 values. The estimated parameters are 80 4.40, a₁ = 1.60, a2 = 0.70, a3 = 0.24, and the three most recent values are Y₁4 18, Y15=27, and Y16 = 39. Forecast the values for the next year and the following year. Y17-(Type an integer or a decimal.)

A third-order autoregressive model is fitted to an annual time series with 16 values. The estimated parameters are 80 4.40, a₁ = 1.60, a2 = 0.70, a3 = 0.24, and the three most recent values are Y₁4 18, Y15=27, and Y16 = 39. Forecast the values for the next year and the following year. Y17-(Type an integer or a decimal.)

Advanced Engineering Mathematics
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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A third-order autoregressive model is fitted to an annual time series with 16 values. The estimated parameters are ao 4.40, a₁ = 1.60, a2=0.70, ag=0.24, and the three most recent values are Y14 =18, Y15 = 27, and Y16 = 39. Forecast the values for the next year and the following year. 17(Type an integer or a decimal.)
Transcribed Image Text:A third-order autoregressive model is fitted to an annual time series with 16 values. The estimated parameters are ao 4.40, a₁ = 1.60, a2=0.70, ag=0.24, and the three most recent values are Y14 =18, Y15 = 27, and Y16 = 39. Forecast the values for the next year and the following year. 17(Type an integer or a decimal.)
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