Uppgift 13: Consider the following time series data:Month 1 2 3 4567Value 24 13 20 12 19 23 15Use a smoothing constant a = 0.2 to compute the exponential smoothingforecasts for the time series. Compute MSE, and a forecast for week 8.Use a smoothing constant of a = 0.4 to compute the exponential smoothinga.b.forecasts.Does a smoothing constant of 0.2 or 0.4 appear to provide more accurateforecasts based on MSE? Explain.A complete answer should be given that is easy to follow step by step.C.

In order to forecast for the period t+1 using the values (actual value At and forecasted value Ft)…

Answered: Uppgift 13: Consider the following time…

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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Given the following data, calculate the three-month moving average forecasts formonths 4, 5, 6, and 7
The data for this problem are the air freight shipments (in ton-miles) each month (beginning in January for one year) in the U. S. for 10 years. The following is a time series plot of this data. What are the most important features of this plot? Ton-miles 3000- 2500- 2000- 1500- 1000- 1 Time Series Plot of Ton-miles ܚ ܪܘܐܐܐ ܘ ܚܐ ܀ 12 24 36 48 60 Index 72 84 96 108 120
Q. 2 Describe the method of Moving averages for estimating the trend in a time series
1.8 Compute and compare the total electricity consumption of Sub-Saharan Africa to the United States in 2012. The population of Sub-Saharan Africa was 926 million, and the United States was 314 million. The per person consumption in the United States in 2012 was 12.96 MWh per year. Consult Fig. 1.11 for the per person consumption in Sub-Saharan Africa.
Given the number of calls per week received by a dental clinic, what is the forecasted number of calls for week 12 considering that the forecast for week 1 was 47 and a smoothing constant a -0.2? CALLS 52 35 25 36 45 35 44 WEEK 1 2 3 4 5 6 7 869 10 34 calls 35 calls 33 calls 38 calls 30 35 25
Please answer the following question using the images provided for data in the images. 1. Which of the following time periods will have the largest annual average increase in the percentage of jobs that could be fully automated (based on the provided images attached)? A) 2020-2028 B) 2028-2030 C) 2030-2035 D) 2035-2040 E) 2040-2050
Q. 14 Explain the Graphic method of trend estimation in a time series and give its merits and demerits.
Consider the following time series data. Month 1. 3 4 5 7 Value 20 11 19 11 19 22 15 Round your answers to two decimal places. a. Compute MSE using the most recent value as the forecast for the next period. Mean squared error is What is the forecast for month 8? b. Compute MSE using the average of all data available as the forecast for the next period. Mean squared error is What is the forecast for month 8? c. Which method appears to provide the better forecast? - Select your answer -
In Table L-1, the total value of imports of Indonesian goods and services from China for the 2010-2019 period is reported on a quarterly basis. With this data you are asked to analyze it with the Trend model and Seasonal Index. Question: a. Calculate a moving average with the average period length of 4 or MA (4) [why four?] And put the results in a column. Beware of selecting the rows to place the average result. b. Calculate the moving average with the length of the average period is 2 from the data in column MA (4) and the result is given the symbol MA (2x4) and the result is placed in a column. Beware of selecting the rows to place the average result. c. Calculate the ratio to the Moving Average (Y / MA (2x4)) and place it in a new column! d. Calculate a seasonal index and interpret the results! e. Create a Deseasonalized data series and place it in a new column! f. Plot the Dessasonalized data series and read the long-term movement patterns of data! Remember that understanding of…
Consider the time series data in the table below (a-c all count as one problem) a. Construct a time series plot. What type of pattern exists in the data?b. Develop a three-week moving average for this time series. Compute MSEand a forecast for week 8. c. Use α = 0.2 to compute the exponential smoothing value for the time series.Compute MSE and a forecast for week 8.

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