Fill in the table by preparing forecasts based on a five-year moving average, a three-year moving average, and exponential smoothing (w = 0.9 andw = 0.3). (Note: The exponential smoothing forecasts may be begun by assuming Ŷt + 1 = Yt.)Year20002001200220032004200520062007200820092010Actual Demand1,4001,3901,4251,4301,4801,5001,4901,5251,5301,580*Moving Average(5-year)(3-year)Exponential Smoothing(W = 0.3)(W = 0.9) Year (5-year)20055,62520062,02520073,6002,0255,62520082009RMSESquare ErrorMoving Average(3-year)3,0254001,2256254,225O Exponential smoothing (w = 0.3)Exponential smoothing (w = 0.9)Exponential Smoothing(W = 0.9)(W = 0.3)6254,489641,3691,1563,721642,3047,056Based on the RMSE criterion, which of the forecasting methods is the most accurate?O Five-year moving averageO Three-year moving average2,601

Given information:The table for the year and the actual value are given.

Answered: Fill in the table by preparing…

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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The following table contains the demand from the last 10 months: MONTH ACTUAL DEMAND 1 31 2 34 3 33 4 35 5 37 6 36 7 38 8 40 9 40 10 41 a. Calculate the single exponential smoothing forecast for these data using an α of 0.30 and an initial forecast ( F1�1 ) of 31. Note: Round your intermediate calculations and answers to 2 decimal places. b. Calculate the exponential smoothing with trend forecast for these data using an α of 0.30, a δ of 0.30, an initial trend forecast ( T1�1 ) of 1, and an initial exponentially smoothed forecast ( F1�1 ) of 30. Note: Round your intermediate calculations and answers to 2 decimal places. c-1. Calculate the mean absolute deviation (MAD) for the last nine months of forecasts. Note: Round your intermediate calculations and answers to 2 decimal places. c-2. Which is best? multiple choice Exponential smoothing with trend forecast Single exponential smoothing forecast
1 - A simple exponential smoothing model has a current mean of 156.8. Assuming demand for next period is 170, update the value of the smoothing statistic. Let a = 0.1. 2- An electronics company has sold 145, 157, 124, 169,179, 201, 197, and 230 units of a certain stereo system quarterly for the past two years. Plot the data and fit an appropriate model. Forecast sales for the next two quarters.
the following information, Find the forecast for period two using exponential smoothing and a = 0.3. Period 2 Demand 64 70 A Forecast 59
The following data represent a portion of quarterly net sales (in $ millions) of Lowe's Companies, Inc., over five years. Net Sales 8861 10169 1 9984 Source: All data retrieved from Annual Reports for Lowe's Companies, Inc. Click here for the Excel Data File a-1. Estimate an exponential trend model with seasonal dummy variables. (Round your answers to 4 decimal places.) Year 2004 2004 2008 Intercept d1 d2 d3 t Variable Quarter 1 2 1 1 Se Exponential Trend A 1 Year 2 2004 3 2004 4 2004 5 2004 6 2005 7 2005 8 2005 9 2005 10 2006 11 2006 12 2006 13 2006 14 2007 15 2007 16 17 2007 2007 2008 18 19 2008 2008 20 21 2008 B Quarter 123-AWNA W NAWN-AW23 4 4 3 4 4 4 C Net Sales 8861 10169 9064 8550 9913 11929 10592 10808 11921 13389 11211 10406 12172 14167 11565 10379 12009 14509 11728 9984
Period 1 2 3 4 5 6 7 Actual 42 41 39 43 45 F ? ? 2 2. Using the same table above, compute the weighted moving average forecast for demand for four latest period. With data using a weight of .40 for the most recent, .30 for the next recent, .20 the next, and .10 for the oldest. Assume actual demand for period 6 is 44, what is the forecast for period 7?
Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the exponential smoothing method to forecast the number of sales to expect next month. Use the following value of alpha: 0.2. Month Demand Forecast 1 308 349.2 2 388 340.9 3 344 350.3 4 400 349.1 5 341 359.3
The following are historical demand data: ACTUAL YEAR 2011 SEASON DEMAND Spring 201 Summer 142 Fall 380 Winter 578 2012 Spring 469 Summer 273 Fall Winter 683 963 Use regression analysis on deseasonalized demand to forecast demand in summer 2013. (Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecast for summer 2013
Use regression analysis on deseasonalized demand to forecast demand in summer 2013. Forecast for summer 2023 ______
Using exponential smoothing, calculate the forecasts for months 2, 3, 4, 5, and 6. Thesmoothing constant is 0.2, and the old forecast for month 1 is 245.
Need a Net balance graph for the given data

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