
This model demonstrates how you can create a Boolean vector identifying the location of the minimum or maximum items in a vector of values.

This model demonstrates how you can take a scalar value and add it to one of the items of a vector using an Expression. It includes an illustrative Dashboard.

This model addresses the need to randomly order a given number of indexed items

This model demonstrates the various ways in which array constructors can be used to construct vectors or matrices from different inputs.

Example model illustrating adding a vector to an existing matrix

This model integrates (accumulates) a scalar daily signal over a period of 5 years and returns monthly and annual sums.

Methods to calculate the median of an array or time series are illustrated using Script elements and Function elements.

Take any vector of values and rank them according to their respective value from highest to lowest or the opposite.

This model shows how scalar and vector daily signals can be integrated to obtain annual sums stored in a vector or matrix format.

This model shows how a vector daily signal can be integrated to obtain monthly sums stored in a matrix format.

This model illustrates how to load values from a matrix into a vector and from a vector into a matrix. This can be done using GoldSim's vector and matrix constructors.

This example shows how to use a vector constructor to generate a vector of month flow rates for integration and other calculations

This model illustrates how you can add Select All and Select None functionality to check boxes in a GoldSim Dashboard.

Use a Script element to replace the Splitter element for vector input types

Use a Script element to replace the Allocator element for vector input types

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

This example shows how a vector of sampled values can be generated from a single distribution definition for Sampled, Cumulative and Discrete stochastics

This example shows how to define and sample vector discrete and cumulative distributions using (1) a vector uniform 01 stochastic to sample probability levels and (2) a script element to get the corresponding values.

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

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

Watershed runoff is calculated for three catchments using the same function but different inputs

Calculate future, monthly water demands based on current usage and an annual projection