Macros for Time Series

1. Area Under a Connect Line
2. Cross Correlations for Multiple Pairs of Columns
3. Mann-Kendall Test for Detecting Trends
4. Median Smoother
5. Sen's Slope
6. Spectral Analysis
7. Winters' Additive Model: Prediction Intervals for Forecasts
8. Winters' Multiplicative Model: Prediction Intervals for Forecasts

Area Under a Connect Line
This macro calculates the area under a connect line, which has application in Genetics, Plant Pathology, Agronomy, Nematology, Breeding Entomology, etc. Specifically, it may be beneficial to those interested in the area under the disease-progress curve (AUDPC). Written by Eli Walters Back to Top

• Minitab 15 and 16
• Code
  

Cross Correlations for Multiple Pairs of Columns
This macro computes cross correlations for two or more pairs of columns. Written by Andy Haines Back to Top

• Minitab 15 and 16
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Mann-Kendall Test for Detecting Trends
This macro calculates the Mann-Kendall test for detecting trends in data collected over time. An adjustment is made for tied observations in this non-parametric test. You must have at least 10 observations for the Normal approximation to be appropriate. Written by Cathy Akritas Back to Top

• Minitab 15 and 16
• Code
  

Median Smoother
This macro calculates a median smoother with a default span of 3. The 1st observation of the smoothed data is the median of the 1st 3 data points (X1, X2, X3). The 2nd observation of the smoothed data is the median of the (X2, X3, X4). The 3rd observation is the median of (X3, X4, X5)… Thus, the smoothed data represents a moving median of the original data. Written by Cathy Akritas Back to Top

• Minitab 15 and 16
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Sen's Slope
This macro calculates Sen's Slope which is a nonparametric alternative for estimating a slope for a univariate time series. This approach involves computing slopes for all the pairs of ordinal time points and then using the median of these slopes as an estimate of the overall slope. Sen's slope is insensitive to outliers and can be used to detect if there is a trend in the data. Written by Cathy Akritas Back to Top

• Minitab 15 and 16
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Spectral Analysis
This macro provides the following tools for spectral analysis: the periodogram, the cumulative periodogram, the estimated spectral function, and spectral model checking. These functions are very valuable for stationary processes and provide frequency analysis methods for residual and ARIMA model diagnostics. Written by Steve Orlich Back to Top

• Minitab 15 and 16
• Code
  Sample Data 1
  Documentation
  

Winters' Additive Model: Prediction Intervals for Forecasts
This macro allows you to specify a confidence level other than 95% for the prediction intervals for the forecasts when using Winters' Method additive model is appropriate. Written by Andy Haines Back to Top

• Minitab 15 and 16
• Code
  

Winters' Multiplicative Model: Prediction Intervals for Forecasts
This macro allows you to specify a confidence level other than 95% for the prediction intervals for the forecasts when using Winters' Method and a multiplicative model is appropriate. Written by Andy Haines Back to Top

• Minitab 15 and 16
• Code
  

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Minitab Inc. provides the Macro Library as a convenience only. Minitab neither endorses, supports, nor verifies the accuracy of any content, information, or functionality of any macro found in the Macro Library. Minitab specifically disclaims any and all responsibility or liability arising from or related to any reliance upon, use, or incorporation of any content, information, or macro found in the Macro Library.