Performs a bootstrap calculation on the supplied data set for the given statistic. The default implementation utlizes a random resampling with replacement. Other resampling methods may be defined by specifying an appropriate routine by means of the method input. The module provides another option, random_resample, which is a parametric Gaussian bootstrap based on the sample mean and standard deviation. It assumes normally distributed observations. The confidence limits are percentile intervals calculated from the bootstrap replicates.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| procedure(bootstrap_statistic_routine), | intent(in), | pointer | :: | stat |
The routine used to compute the desired statistic. |
|
| real(kind=real64), | intent(in), | dimension(:) | :: | x |
The N-element data set. |
|
| procedure(bootstrap_resampling_routine), | intent(in), | optional, | pointer | :: | method |
An optional pointer to the method to use for resampling of the data. If no method is supplied, a random resampling is utilized. |
| integer(kind=int32), | intent(in), | optional | :: | nsamples |
An optional input, that if supplied, specifies the number of bootstrap replicates to generate. The default is 10 000. |
|
| real(kind=real64), | intent(in), | optional | :: | alpha |
An optional input, that if supplied, defines the significance level to use for the analysis. The default is 0.05. |
The resulting bootstrap_statistics type containing the confidence intervals, bias, standard error, etc. for the analyzed statistic.