Ma eliminates bad data after n periods after ma

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: ES carries all past history. MA eliminates “bad” data after N periods after MA requires all N past data points while ES only requires last forecast and last observation. requires 12 Regression Analysis Regression Methods can be used when a trend is present. Let (x1, y1)…. be n paired data points for two present. )…. variables which x iis the independent variable and y iis the s s dependent one (on x). ˆ y = a + bx ˆ y is the predicted value of the response y. In forecasting problems, usually the independent variable x iis time, t. s We have to estimate the values of a and b. and Regression Analysis b= N ∑ ty − ∑ t ∑ y 2 N ∑ t − (∑ t ) a= 2 ∑ y − b∑ t N 13 Example Year 1 2 3 4 5 6 7 8 9 10 Sales 1000 1300 1800 2000 2000 2000 2200 2600 2900 3200 Seasonality Seasonality corresponds to a pattern in the data that repeats at regular intervals. repeats There may be multiple seasonal factors: c1 , c2 , . . . , cN There where i = 1 is first period of season, i = 2 is second where period of the season, etc.. period ci = 1.25 implies 25% higher than the baseline on avg. ci = 0.75 implies 25% lower than the baseline on avg. 14 Seasonality Illustration Method of Estimating Seasonal Method Factors Factors Compute the sample mean of the entire data set (should be at least several seasons of data). be Divide each observation by the sample mean. (This gives a factor for each observation.) gives Average the factors for like periods in a season. Average The resulting N numbers will ex...
View Full Document

Ask a homework question - tutors are online