Data analysis

Manage data and samples

• A quick start guide to the Point and Sample classes
• Import / export a sample via a CSV file
• Sample manipulation
• Estimate moments from sample
• Correlation analysis on samples
• Build and validate a linear model
• Wilks and empirical quantile estimators
• Interaction with Pandas

Sample analysis

• Visualize an histogram from data
• Compare unconditional and conditional histograms
• Visualize empirical CDF
• Draw the survival of a sample or a distribution

Distribution fitting

• Fit a normal distribution
• Fit a distribution by maximum likelihood
• Non parametric distribution fitting
• Estimate a multivariate distribution

Statistical hypothesis testing

• Test distribution fitting using Kolmogorov
• The Kolmogorov-Smirnov statistics
• The Kolmogorov-Smirnov p-value
• The Kolmogorov-Smirnov distribution
• Distribution fitting test using Chi2
• Distribution fitting test using QQ plot
• Compare samples using Komogorov-Smirnov test, QQ-plot
• Normal fitting test using the Henry line
• Cramer-Von Mises normality test
• Test normality using Anderson-Darling
• Select fitted distributions

Estimate dependency and copulas

• Sample independence test
• Fit a parametric copula
• Fit a non parametric copula
• Copula fitting test using Kendall plot
• Test samples independence using regression
• Graphical copula validation

Estimate stochastic processes

• Estimate a scalar ARMA process
• Estimate a multivariate ARMA process
• Estimate a stationary covariance function
• Estimate a non stationary covariance function
• Estimate a spectral density function

Graphics

• Visualize clouds
• Visualize pairs