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compute-hdc: Highest density contour method in Matlab

version 1.2.4 (389 KB) by Andreas Haselsteiner
A software to compute a highest density environmental contour.

220 Downloads

Updated 7 May 2020

From GitHub

View License on GitHub

# compute-hdc: Highest density contour method in Matlab
![Environmental contour](example-environmental-contour.jpg)

A software to compute a highest density environmental contour.

A highest density (HD) contour is one possible definition for an environmental
contour. This definition has been proposed by Haselsteiner, Ohlendorf,
Wosniok and Thoben (2017; http://doi.org/10.1016/j.coastaleng.2017.03.002)

## Download and use the repository
To download this repository and its submodules use
```console
git clone --recurse-submodules https://github.com/ahaselsteiner/compute-hdc.git
```

## Individual files and functionality
This software involves a couple of .m files for computing a HD contour:
* `computeHdc`: Computes the contour. It needs a probabilistic model,
an exceedance probability and a grid as its input.
* `computeHdcExampleWithCMA`: Cotains examples how to use `computeHdc`.
* `getProbabilisticModel`: Returns some sample probabilistic models,
which can be used with `computeHdc`.
* The other functions are subroutines needed for `computeHdc`.

The software also includes implementations of other environmental contour
methods, which use different definitions for the exceedance probablity
of an environmental contour:
* `computeIFormContour`: Computes an inverse first order reliablity method
(IFORM) contour.
* `computeDsContour`: Computes a direct sampling contour.
* `computeISormContour`: Computes an inverse second order reliablity method
(ISORM) contour.

Cite As

Andreas Haselsteiner (2022). compute-hdc: Highest density contour method in Matlab (https://github.com/ahaselsteiner/compute-hdc), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2016b
Compatible with any release
Platform Compatibility
Windows macOS Linux

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To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.