Data analysis

Manage data and samples

Link Pandas and OpenTURNS

Randomize the lines of a Sample

Import / export a sample via a CSV file

Estimate moments from sample

Sample manipulation

Sort a sample

A quick start guide to the Point and Sample classes

Estimate Wilks and empirical quantile

Build and validate a linear model

Estimate correlation coefficients

Sample analysis

Draw an histogram

Draw the empirical CDF

Compare unconditional and conditional histograms

Draw a survival function

Distribution fitting

Fit a distribution by maximum likelihood

Fit a parametric distribution

Model a singular multivariate distribution

Get the asymptotic distribution of the estimators

Bandwidth sensitivity in kernel smoothing

Fit an extreme value distribution

Estimate a conditional quantile

Estimate a multivariate distribution

Fit a non parametric distribution

Statistical tests

Test a discrete distribution

Draw the QQ-Plot

Use the Kolmogorov/Lilliefors test

Test identical distributions

Select fitted distributions

Test Normality

Test independence

Test the copula

Kolmogorov-Smirnov : understand the statistics

Kolmogorov-Smirnov : understand the p-value

Kolmogorov-Smirnov : get the statistics distribution

Estimate dependency and copulas

Fit a parametric copula

Fit a non parametric copula

Estimate stochastic processes

Estimate a multivariate ARMA process

Estimate a non stationary covariance function

Estimate a scalar ARMA process

Estimate a spectral density function

Estimate a stationary covariance function

Graphics

Visualize pairs

Visualize clouds

Visualize sensitivity