OpenTURNS
Probabilistic modeling¶
Distributions¶
- Create univariate and multivariate distributions: a quick start guide to distributions
- Overview of univariate distribution management
- Create a gaussian distribution
- Create a geometric distribution
- Draw 1-d distribution graphs
- Create a truncated distribution
- Create a 2-d gaussian distribution
- Draw 2-d distribution graphs
- Create a composed distribution
- Random vector manipulation
- Distribution manipulation
- Creation of a custom random vector
- Creation of a custom distribution or copula
- Create a mixture of PDFs
- Create a random mixture of distributions
- Create a discrete random mixture
- Transform a distribution
- Create a composite distribution
- Composite random vector
- Create a maximum distribution
- Create a conditional distribution
- Create a conditional random vector
- Create a Bayes distribution
- Draw minimum volume level set in 1D
- Draw minimum volume level set in 2D
- Generate random variates by inverting the CDF
Copulas¶
Stochastic processes¶
- Creation of a mesh
- Creation of a regular grid
- Process manipulation
- Field manipulation
- Time series manipulation
- Process sample manipulation
- Create a stationary covariance model
- Create a custom stationary covariance model
- Create a custom covariance model
- Comparison of covariance models for gaussian processes
- Create a gaussian process from a cov. model
- Create a gaussian process from a cov. model using HMatrix
- Create a gaussian process from spectral density
- Create a parametric spectral density function
- Create a custom spectral model
- Create an ARMA process
- ARMA process manipulation
- Create a white noise process
- Create a random walk process
- Create a discrete Markov chain process
- Create a functional basis process
- Add a trend to a process
- Trend computation
- Apply a Box-Cox transformation to a Field
- Aggregate processes