code: def isValidEstimatorParams(p):
    
    if not isinstance(p, dict):
      return False
    if "distribution" not in p:
      return False
    if "movingAverage" not in p:
      return False
    dist = p["distribution"]
    if not ("mean" in dist and "name" in dist
            and "variance" in dist and "stdev" in dist):
      return False
  
    return True
docs: :returns: ``True`` if ``p`` is a valid estimator params as might be returned
      by ``estimateAnomalyLikelihoods()`` or ``updateAnomalyLikelihoods``,
      ``False`` otherwise.  Just does some basic validation.