AbstractMarkov chain Monte Carlo methods and computer simulations usually use long sequences of random numbers generated by deterministic rules, so-called pseudorandom number generators. Their efficiency depends on the convergence rate to the stationary distribution and the quality of random numbers used for simulations. Various methods have been employed to measure the convergence rate to the stationary distribution, but the effect of random numbers has not been much discussed. We present how to test the efficiency of pseudorandom number generators using random walks
AbstractFor any finite sequence of (pseudo)random numbers special simulation problems can be constru...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
The statistical properties of a pseudorandom sequence being characterized by the distribution of the...
Includes bibliographical references (pages 91-93)This paper is an examination of the generation of r...
In Monte Carlo calculations performed on electronic computers it is advantageous to use an arithmeti...
We propose three physical tests to measure correlations in random num-bers used in Monte Carlo simul...
Abstract: The problem of generating sequences of uniformly distributed pseudorandom numbers is consi...
Monte Carlo computations are considered easy to parallelize. However, the results can be adversely a...
So-called Random number generators on computers are deterministic functions producing a sequence of ...
Pseudorandom number generators are widely used in the area of simulation. Defective generators are s...
Parallel computers are now commonly used for computational science and engineering, and many applica...
Monte Carlo simulations have become a common practice to evaluate a proposed statistical procedure, ...
This thesis is related to varies statistical test of pseudorandom number generator. In thisthesis I ...
It is well known that there are no perfectly good generators of random number sequences, implying th...
Several pseudorandom number generators are described and compared on the basis of cost of generation...
AbstractFor any finite sequence of (pseudo)random numbers special simulation problems can be constru...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
The statistical properties of a pseudorandom sequence being characterized by the distribution of the...
Includes bibliographical references (pages 91-93)This paper is an examination of the generation of r...
In Monte Carlo calculations performed on electronic computers it is advantageous to use an arithmeti...
We propose three physical tests to measure correlations in random num-bers used in Monte Carlo simul...
Abstract: The problem of generating sequences of uniformly distributed pseudorandom numbers is consi...
Monte Carlo computations are considered easy to parallelize. However, the results can be adversely a...
So-called Random number generators on computers are deterministic functions producing a sequence of ...
Pseudorandom number generators are widely used in the area of simulation. Defective generators are s...
Parallel computers are now commonly used for computational science and engineering, and many applica...
Monte Carlo simulations have become a common practice to evaluate a proposed statistical procedure, ...
This thesis is related to varies statistical test of pseudorandom number generator. In thisthesis I ...
It is well known that there are no perfectly good generators of random number sequences, implying th...
Several pseudorandom number generators are described and compared on the basis of cost of generation...
AbstractFor any finite sequence of (pseudo)random numbers special simulation problems can be constru...
In the classical approach to pseudo-random number generators, a generator is considered to perform w...
The statistical properties of a pseudorandom sequence being characterized by the distribution of the...