anchor.diff:  == normalizeSum
   
   The `normalizeSum` function scales numeric arrays so that they sum to 1.
  -The normalizeSum function can operate on both numeric arrays and matrices.
  -
  -When operating on a matrix the normalizeSum function operates on each row of the matrix.
  +The `normalizeSum` function can operate on both numeric arrays and matrices.
  +
  +When operating on a matrix the `normalizeSum` function operates on each row of the matrix.
   
   === normalizeSum Parameters
   
  -* `numeric array` | matrix
  +* `numeric array` | `matrix`
   
   === normalizeSum Syntax
   
  
positive.code: == markovChain
  
  The `markovChain` function can be used to perform https://en.wikipedia.org/wiki/Markov_chain[Markov Chain] simulations.
  The markovChain function takes as its parameter a https://en.wikipedia.org/wiki/Stochastic_matrix[transition matrix] and
  returns a mathematical model that can be sampled using the <<sample>> function. Each sample taken
  from the Markov Chain represents the current state of system.
  
  
negative.code: 
  == minMaxScale
  
  The `minMaxScale` function scales numeric arrays within a minimum and maximum value.
  By default `minMaxScale` scales between 0 and 1. The `minMaxScale` function can operate on
  both numeric arrays and matrices.
  
  When operating on a matrix the `minMaxScale` function operates on each row of the matrix.
  
  === minMaxScale Parameters
  
  * `numeric array` | `matrix`: The array or matrix to scale
  * `double`: (Optional) The min value. Defaults to 0.
  * `double`: (Optional) The max value. Defaults to 1.
  
  === minMaxScale Syntax
  
  