Time-series re-indexing
Type: Model example, Extra
This model contains some examples of time-series re-indexing. It is intended to demonstrate some of these basic techniques.
In this example, actual measurements were collected at non-uniform time increments. Before analyzing these, we map these to a uniformly spaced time index (Week), occurring on Monday of each week. The mapping is done using an interpolation. The evenly-spaced data is then used to forecast future behavior. We first forecast over an index containing only future time points (Future_weeks), using a log-normal process model based on the historical weekly change. We then combine the historical data with the forecast on a common index (Week). A prob-bands graph of the weekly_data result shows the range of uncertainty projected by the process model (you'll notice the uncertainty exists only for future forecasted values, not historical ones).
Download: Time-series-reindexing.ana
Author: Lonnie Chrisman
Keywords: Arrays, Mathematics and science, Time series, Dynamic models, forecasting, time-series re-indexing