# stats - Statistics#

## gammapy.stats Package#

Statistics.

### Functions#

 cash(n_on, mu_on[, truncation_value]) Cash statistic, for Poisson data. cash_sum_cython(counts, npred) Summed cash fit statistics. cstat(n_on, mu_on[, truncation_value]) C statistic, for Poisson data. f_cash_root_cython(x, counts, background, model) Function to find root of. get_wstat_gof_terms(n_on, n_off) Goodness of fit terms for WSTAT. get_wstat_mu_bkg(n_on, n_off, alpha, mu_sig) Background estimate mu_bkg for WSTAT. norm_bounds_cython(counts, background, model) Compute bounds for the root of _f_cash_root_cython. wstat(n_on, n_off, alpha, mu_sig[, mu_bkg, ...]) W statistic, for Poisson data with Poisson background. compute_fvar(flux, flux_err[, axis]) Calculate the fractional excess variance. compute_fpp(flux, flux_err[, axis]) Calculate the point-to-point excess variance. compute_flux_doubling(flux, flux_err, coords) Compute the minimum characteristic flux doubling and halving over a certain coordinate axis for a series of measurements. compute_chisq(flux) Calculate the chi-square test for LightCurve. structure_function(flux, flux_err, time[, ...]) Compute the discrete structure function for a variable source. TimmerKonig_lightcurve_simulator(...[, ...]) Implementation of the Timmer-Koenig algorithm to simulate a time series from a power spectrum.

### Classes#

 CashCountsStatistic(n_on, mu_bkg) Class to compute statistics for Poisson distributed variable with known background. WStatCountsStatistic(n_on, n_off, alpha[, ...]) Class to compute statistics for Poisson distributed variable with unknown background.