anchor.diff:  `mse`:: Mean squared error or rather `rss` divided by the number of documents consumed for model estimation.
   `coefficients`:: Slope coefficients
     image:http://latex.codecogs.com/gif.latex?\theta_1,%20\theta_2,%20\theta_3,.%20.%20.,%20\theta_C%20[]
  -    of the linear function estimated regarding least-squares regression.
  +    of the linear linear hypothesis function ``h(x)``.
   `intercept`:: Intercept coefficient image:http://latex.codecogs.com/gif.latex?\theta_0%20[]
  -                 of the linear function estimated regarding least-squares regression.
  +                 of the linear hypothesis function ``h(x)``.
   
   
   ## Installation
  
positive.code: 
  
  ## Aggregations
  The aggregations estimate the linear regression coefficients
  image:http://latex.codecogs.com/gif.latex?\theta_0,%20\theta_1,%20\theta_2,.%20.%20.,%20\theta_C%20[]
  based on document results of a search query. Each search result
  document is handled as an observation and the numerical fields as variables (explanatory and response)
  
negative.code: 
  === Linear Regression Stats
  
  The `linreg_stats` aggregation computes statistics for the estimated linear regression model.
  
  [horizontal]
  `rss`:: Residual sum of squares as a measure of the discrepancy between the data and the estimated model.
  