class_docstr: Compute metric pairwise.
  
  Parameters
  ----------
  func : function
      Function that computes the pairwise metric.
  
  name : str
      Name of the metric
docstr: Compute metric and standard error.
  
  References
  ----------
  .. [1] Efron and Stein, (1981), "The jackknife estimate of variance."
  
  .. [2] McIntosh, Avery. "The Jackknife Estimation Method".
      <http://people.bu.edu/aimcinto/jackknife.pdf>
  
  .. [3] Efron, Bradley. "The Jackknife, the Bootstrap, and other
      Resampling Plans". Technical Report No. 63, Division of
      Biostatistics,
      Stanford University, December, 1980.
  
  .. [4] Jackknife resampling
  <https://en.wikipedia.org/wiki/Jackknife_resampling>
code: def compute(self, y_true, y_pred):
      """Compute metric and standard error.
  
      References
      ----------
      .. [1] Efron and Stein, (1981), "The jackknife estimate of variance."
  
      .. [2] McIntosh, Avery. "The Jackknife Estimation Method".
          <http://people.bu.edu/aimcinto/jackknife.pdf>
  
      .. [3] Efron, Bradley. "The Jackknife, the Bootstrap, and other
          Resampling Plans". Technical Report No. 63, Division of
          Biostatistics,
          Stanford University, December, 1980.
  
      .. [4] Jackknife resampling
      <https://en.wikipedia.org/wiki/Jackknife_resampling>
      """
      # compute aggregate metric
      mean = self.func(y_true, y_pred, **self.kwargs)
  
      # compute stderr based on jackknifed metrics
      n_instances = len(y_true)
      index = np.arange(n_instances)
  
      # get jackknife samples of index
      jack_idx = self._jackknife_resampling(index)
  
      # compute metrics on jackknife samples
      jack_pointwise_metric = np.array(
          [
              self.func(y_true[idx], y_pred[idx], **self.kwargs)
              for idx in jack_idx
          ]
      )
  
      # compute standard error over jackknifed metrics
      jack_stderr = self._compute_jackknife_stderr(
          jack_pointwise_metric
      )
      return mean, jack_stderr
  
file_path: sktime/sktime/benchmarking/metrics.py
imports: import numpy
  from sktime.benchmarking.base import BaseMetric
label_desc: Use image node_id 2 for calling the AggregateMetric obj's underlying member method code with example usage: obj.compute(y_true, y_pred) and returns: mean,  jack_stderr