Data analysis¶
Manage data and samples¶
Randomize the lines of a Sample
Import / export a sample via a CSV file
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¶
Compare unconditional and conditional histograms
Compute squared SRC indices confidence intervals
Distribution fitting¶
Fit a distribution by maximum likelihood
Model a singular multivariate distribution
Define a distribution from quantiles
Get the asymptotic distribution of the estimators
Estimate a GEV on the Venice sea-levels data
Bandwidth sensitivity in kernel smoothing
Fit an extreme value distribution
Estimate a conditional quantile
Estimate a multivariate distribution
Estimate a GPD on the Wooster temperature data
Estimate a GPD on the Dow Jones Index data
Fit a non parametric distribution
Fitting a distribution with customized maximum likelihood
Estimate a GEV on the Port Pirie sea-levels data
Estimate a GPD on the daily rainfall data
Estimate a GEV on race times data
Estimate a GEV on the Fremantle sea-levels data
Statistical tests¶
Use the Kolmogorov/Lilliefors test
Kolmogorov-Smirnov : understand the p-value
Kolmogorov-Smirnov : understand the statistics
Kolmogorov-Smirnov : get the statistics distribution
Estimate dependency and copulas¶
Estimate tail dependence coefficients on the wave-surge data
Estimate tail dependence coefficients on the wind data
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