class_docstr: Estimation of a value based on one or multiple evaluations.
  This class provides easy access to:
  - count: how many times the point was evaluated
  - mean: the mean value.
  - square: the mean square value
  - variance: the variance
  - parameter: the corresponding Parameter
  
  
  It also provides access to optimistic and pessimistic bounds for the value.
  
  Parameter
  ---------
  parameter: Parameter
      the parameter for one of the evaluations
  y: float
      the first evaluation of the value
code: def optimistic_confidence_bound(self) -> float:
      return float(
          self.mean - 0.1 * np.sqrt((self.variance) / (1 + self.count))
      )
  
imports: import math
  import operator
  import numpy
  from nevergrad.parametrization import parameter
  from nevergrad.parametrization.utils import float_penalty
  import nevergrad.common.typing
  from nevergrad.common.tools import OrderedSet
label_desc: Use image node_id 3 for calling the MultiValue obj's underlying member method code with example usage: obj.optimistic_confidence_bound() and returns: float