iCLIP.random.boot_ci

iCLIP.random.boot_ci(x, quantiles=(0.05, 0.95), *args, **kwargs)

Calculate confidence intervals on the results of function using bootstrapping.

Parameters:
  • x (pandas.Series or pandas.DataFrame) – Object containing data to bootstrap from
  • quantiles (tuple of (float, float), optional) – quantiles to use in calculating confidence interval. For example, for a 95% confidence interval, supply (0.025, 0.975)
  • **kwargs (*args,) –

    further arguments and keyword arguements passed to bootstrap() (and likely onwards to the function called by bootstrap).
Returns:

Series with the specified quantiles from the bootstraps
Return type:

pandas.Series
Other Parameters:
 
  • fun (func) – function to be applied to bootstrap samples of x
  • bootstraps (int) – number of bootstrap samples to use_args

See also

bootstrap()
draw bootstrap samples and apply a function to eaach
ratio_and_ci()
Uses this function to calculate confidence intervals on the ratio of two columns.