Time Series & Lookup Tables
Models Illustrating the Use of Time Series and Lookup Tables
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Methods to calculate the median of an array or time series are illustrated using Script elements and Function elements.

This model illustrates how to fit a trend line to data using the GaussNewton method.

The purpose of this model is to demonstrate time shifting historic data in a Time Series element. This type of model makes it easy to show summary statistics like exceedance probability of annual peak flow rate or mean annual flow rate.

This model includes 4 different methods of time shifting to be used in a wider array of applications.

This model illustrates how you can reference a Time Series like a lookup function to access future or past values.

Example model which generates probabilistic time histories and postprocesses time history statistics

Uses SubModels to preprocess (and plot) historic time series data

This example shows how to import 1D, 2D and 3D Lookup Table data from text and Excel files.

Examples illustrating basic Time Series element functionality

This model provides an example of calculating statistics for a data time series.

This model provides examples of two different methods which can be used to generate statistics for time histories.

This model plots paired data for equivalent time intervals on the same scatterplot.

This model creates a histogram from time series values and uses it to create a PMF of the data.

In this example, a SubModel is used to calculate average monthly rainfall amounts from a Time Series element containing rainfall rate data

This model implements a spline interpolation method to generate smoothlyvarying dependent variable values from a 1D Lookup Table.

Operating rules control outflows from a reservoir that contains operating zones divided into surcharge, flood control, conservation, and dead pool zones.
Making
Better Decisions
In An
Uncertain World