Time Series with Minitab
Smoothing
I. Moving average:
On menu:
Stat>Time Series>Moving Average
Variable – column holding the series
MA length – number of periods to be averaged
“Generate forecasts” - check this and enter
Number of forecasts – 1
Starting from origin – [fill in number of last observation – if you have 20 items, enter 20, if 15 data points, enter 15)
*To see the “forecasts” for
the past data (Minitab will call these values “fits”)
Click “Storage”
Select “moving averages” and “Fits(one-period-ahead-forecasts)”
Result (in Session window) gives:
Moving average
Length [tells unumber of periods)
Accuracy measures – We are interested in MSD (text calls it MSE)
Forecast – period (should be next period after data) & forecast. [Don’t worry about upper & lower – that’s an interval estimate we shall not discuss]
*If you chose to store Fits and Averages – these will appear in columns of the data window – averages in “AVER1” (beside the last period included in the average) and prediction in “FITS1”. If you do several series calculations, you’ll get “AVER2”FITS2” “AVER3”FITS3” etc.
II. Exponential Smoothing:
On menu
Stat>Time Series> Single Exp Smoothing
Variable – column holding the series
MA length – number of periods to be averaged
“Generate forecasts” - check this and enter
Number of forecasts – 1
Starting from origin – [fill in number of last observation – if you have 20 items, enter 20, if 15 data points, enter 15)
Click “Options”
“Use average of first K observations, K = “ enter 1
*To see the “forecasts” for
the past data (Minitab will call these values “fits”)
Click “Storage”
Select “Smoothed Data” “Fits(one-period-ahead-forecasts)” and
Result (in Session window) gives:
Data – column name
Length – (number of data points)
Smoothing Constant Alpha
Accuracy measures – We are interested in MSD (text calls it MSE)
Forecast – period (should be next period after data) & forecast. [Don’t worry about upper & lower – that’s an interval estimate we shall not discuss]
*If you chose to store Smoothed data and Fits – these will appear in columns of the data window – averages in “SMOO1” (beside the period used to calculate) and prediction in “FITS1”. If you do several series calculations, you’ll get “SMOO2”FITS2” “SMOO”FITS3” etc.
با تشکر از کسانی که با نظرات و انتقادهای خود باعث بالا رفتن کیفیت وبلاگ می شوند.