**MAD Statistics for Time-Series Models**The following is the list of MAD (Mean Absolute Deviation) statistics for each of the models you have estimated from time-series data:| Model | MAD ||---------------------|------|| Linear Trend | 2.38 || Quadratic Trend | 3.22 || Exponential Trend | 1.39 || AR(2) | 2.71 |Based on the MAD criterion, the most appropriate model is- [ ] AR(2)- [ ] exponential trend- [ ] linear trend- [ ] quadratic trend

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Answered: The following is the list of MAD…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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I have entered this question twice, and am still not getting the correct answers, please help. Complete the table by computing the absolute and relative change. Time Value Absolute Change Relative Change 0 12.58 XXXXX XXXXX 1 15.6 2 19.34 3 23.98 4 29.74 5 36.88 (i) Which of the following statements are true? Select all that apply.A. The data suggest that an exponential model would be appropriate.B. The data suggest that a linear model would be appropriate.C. The data increase by a fixed amount each year.D. The data show a constant growth rate.E. No model can be inferred from the data provided. (ii) Use the data from the table to construct the appropriate model to predict the value at future times. What value does your model predict when the time is 7.5?(Express your answer rounded correctly to the nearest hundredth.)Answer =
feyeb St Ral 5. Use regression to determine an exponential model for the following data. Round all parameters to 3 decimals. 15 20 22 10 d 140 250 410 780 1300 1670 CE OTTAS
Ten years of monthly data of a seasonally adjusted series are used to estimate a linear trend model as T = 24.10+ 0.32t. In addition, seasonal indices for January and February are calculated as 1.08 and 0.97, respectively. Make a forecast for the first two months of next year. (Do not round intermediate calculations. Round your answers to 2 decimal places.) ýt January February
G FTSE 100 6. Consider the OLS estimator of a model to explain the stock prices of observations from 2012 m1 to 2021 m 12, all variables are calculated company using 120 at the end of the month t log (stock +) 0.86 + 0.86 + 0.54 log (profit 6) - 0.65 log (research t)-1.34 log (marketing 6) (6.1) (1.12) (0.24) (0.30) (0.12) 3 n = 120, R² = 0.34 SSR = 1.29 F = 3.99 : / " 116 where stuck t the › in millions of stock price in GBP (British Sterling) profit & (the profit before tax GBP), research & (expenditure on research and development), and marketing t marketing) are measured in parentheses, SSR is the Sum of Squared Residuals, and the I statistic for the significance GBP. Standard errors are reported in (expenditure on millions of of the regression is $ provided. lat What is the interpretation of the coefficient on as you would expect? Explain your answer. log (profit t) 7 Is the sign of coefficient measured in thousands of GBP? Explain your answer. Hint: Would your interpretation…

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