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Here <b>sum</b>, <b>mean</b> and <b>variance</b> were inspired by the Peter's inline sum code:

class Array; def sum; inject( nil ) { |sum,x| sum ? sum+x : x }; end; end class Array; def mean; self.sum/self.size.to_f; end; end class Array; def variance; mean = self.mean; Math.sqrt(inject( nil ) { |var,x| var ? var+((x-mean)**2) : ((x-mean)**2)}/self.size.to_f); end; end

If you want to normalize a random variable (array) so that mean = 0 and variance = 1, you can transform your array <b>x</b> by calling:

# inputs a random variable, sets mean = 0 and variance = 1 def standardize_random_variable(x) mean = x.mean variance = x.variance x.map!{|a| (a-mean)/variance } end

If you want to compute distance, call these functions between two arrays of data, a and b.

## Distance Functions # Sum of (x-y)^2 def euclidean_squared_distance(a,b) b = b.to_a a = a.to_a sum_of_diff_sq = 0 (0...a.size).each { |i| sum_of_diff_sq+=((a[i].to_f-b[i].to_f)**2)} sum_of_diff_sq end # Square root of sum of (x-y)^2 def euclidean_distance(neighbor,xq) Math.sqrt(euclidean_squared_distance(neighbor,xq)) end # Sum of abs(x,y) def cityblock_distance(neighbor,xq) xq = xq.to_a abs_diff = 0 (0...xq.size).each { |i| abs_diff+=(Math.abs(xq[i].to_f-neighbor[i].to_f)} abs_diff end

## Comments

## Snippets Manager replied on Sat, 2007/12/08 - 7:18pm