Added superscript for exponents

#40

Author: nmcl

docs/manual.adoc

@@ -389,19 +389,17 @@ public  abstract  class  RandomStream
 
 The multiplicative generator uses the following algorithm:
 
-Y[i+1] = Y[i] * 5^5 mod 2^26
+Y[i+1] = Y[i] * 5^5^ mod 2^26^
 
-THIS NEEDS FIXING!! plus mod superscripted?!
-
-, where the period is 2^24, and the initial seed must be odd (Thanks to Professor I. Mitrani for his help in developing this.)
+, where the period is 2^24^, and the initial seed must be odd (Thanks to Professor I. Mitrani for his help in developing this.)
 
 The uniform() method uses the linear congruential generator (seed is LCGSeed, with the default value of 1878892440L) based on the algorithm in link:http://algs4.cs.princeton.edu/home/[this text], and the results of this are shuffled with the multiplicative generator (seed is MGSeed, with a default value of 772531L) as suggested by link:http://www.amazon.com/Art-Computer-Programming-Volume-Seminumerical/dp/0201896842[Maclaren and Marsaglia], to obtain a sufficiently uniform random distribution, which is then returned.
 
 The error() method returns a chi-square error measure on the uniform distribution function.
 
 By abstract method getNumber must be provided by derived classes, and is used to obtain a uniform means of accessing random numbers.
 
-The  RandomStream class  returns  a  large  sequence  of  random  numbers,  whose  period  is 2^24. However, unless the seeds are modified when each random distribution class is created, the starting position in this sequence will always be the same, i.e., the same sequence of numbers will be obtained. To prevent this, each class derived from RandomStream has an additional parameter for one of its constructors which indicates the offset in this sequence from which to begin sampling.
+The  RandomStream class  returns  a  large  sequence  of  random  numbers,  whose  period  is 2^24^. However, unless the seeds are modified when each random distribution class is created, the starting position in this sequence will always be the same, i.e., the same sequence of numbers will be obtained. To prevent this, each class derived from RandomStream has an additional parameter for one of its constructors which indicates the offset in this sequence from which to begin sampling.
 
 === UniformStream