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Linear congruential generator : ウィキペディア英語版
Linear congruential generator

A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. The method represents one of the oldest and best-known pseudorandom number generator algorithms.〔"(Linear Congruential Generators )" by Joe Bolte, Wolfram Demonstrations Project.〕 The theory behind them is relatively easy to understand, and they are easily implemented and fast, especially on computer hardware which can provide modulo arithmetic by storage-bit truncation.
The generator is defined by the recurrence relation:
: X_ = \left( a X_n + c \right)~~\bmod~~m
where X is the sequence of pseudorandom values, and
: m,\, 0 – the "modulus"
: a,\,0 < a < m – the "multiplier"
: c,\,0 \le c < m – the "increment"
: X_0,\,0 \le X_0 < m – the "seed" or "start value"
are integer constants that specify the generator. If ''c'' = 0, the generator is often called a multiplicative congruential generator (MCG), or Lehmer RNG. If ''c'' ≠ 0, the method is called a ''mixed congruential generator''.
== Period length ==

The period of a general LCG is at most ''m'', and for some choices of factor ''a'' much less than that. The LCG will have a full period for all seed values if and only if:〔

# \,m and the offset \,c are relatively prime,
# \,a - 1 is divisible by all prime factors of \,m,
# \,a - 1 is divisible by 4 if \,m is divisible by 4.
These three requirements are referred to as the Hull-Dobell Theorem. While LCGs are capable of producing pseudorandom numbers which can pass formal tests for randomness, this is extremely sensitive to the choice of the parameters ''c'', ''m'', and ''a''.
Historically, poor choices had led to ineffective implementations of LCGs. A particularly illustrative example of this is RANDU, which was widely used in the early 1970s and led to many results which are currently being questioned because of the use of this poor LCG.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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