anchor.diff:  --------------------------------------------------
   
   The aggregation type is `linreg_stats` and the `fields` setting defines the set of fields (as an array)
  -interpreted as explanatory variables and the last as the response variable for computing the linear
  -regression and the statistics. The above request returns the following response:
  +to be used for building the linear model. The first one to many fields stand for the explanatory variables
  +and the last for the response variable. The above request returns the following response:
   
   [source,js]
   --------------------------------------------------
  
positive.code: 
  Assuming the data consists of documents representing house prices we can compute statistics for
  the estimated best fitting linear hypothesis function which predicts house prices based on number of
  rooms and living space with
  [source,js]
  --------------------------------------------------
  {
      "aggs": {
          "house_prices": {
              "linreg_stats": {
                  "fields": ["rooms", "space", "price"]
              }
          }
      }
  
negative.code:     ...
      "aggregations": {
          "house_prices": {
              "rss": 49523788338938.734,
              "mse": 63410740510.80504,
              "coefficients": [
                  -100544.0725894584,
                  45981.15827544966,
                  309.6013051477475
              ],
              "intercept": 47553.18737564783
          }
      }
  }
  