A sharp estimate of the discrepancy of a concatenation sequence of inversive pseudorandom numbers with consecutive primes

We consider an equidistributed concatenation sequence of pseudorandom rational numbers generated from the primes by an inversive congruential method. In particular, we determine the sharp convergence rate for the star discrepancy of said sequence. Our arguments are based on well-known discrepancy estimates for inversive congruential pseudorandom numbers together with asymptotic formulae involving prime numbers.

Pseudo-random number generator based on linear congruence and delayed Fibonacci method

Pseudo-random number generation techniques are an essential tool to correctly test machine learning processes. The methodologies are many, but also the possibilities to combine them in a new way are plenty. Thus, there is a chance to create mechanisms potentially useful in new and better generators. In this paper, we present a new pseudo-random number generator based on a hybrid of two existing generators - a linear congruential method and a delayed Fibonacci technique. We demonstrate the implementation of the generator by checking its correctness and properties using chi-square, Kolmogorov and TestU01.1.2.3 tests and we apply the Monte Carlo Cross Validation method in classification context to test the performance of the generator in practice.

Penerapan Linear Congruential Method pada Aplikasi Ujian Berbantuan Komputer

In order to obtain information regarding student learning outcomes, the test is one way to go. Both test orally and written test. Along with the development of technology, the current written test is no longer done on paper but done using computer media. Computer-based test is one of the exam types applied in the National Exam and have been implemented in some schools in Indonesia. In this exam, it is possible for students to work on different packages of problems with their colleagues on the side. This is possible because of the problem randomization method. Nevertheless, it should be tested whether in the randomization of the problem has noticed the sequence of occurrences of questions which is still pay attention to the sequence as Bloom Taxonomy. This study focuses on applying the Linear Congruential Method, in order to generate a random problem from the database. The method called Pseudorandom Number Generator. In practice, the Linear Congruential Method method use variables a, c, and m as inputs for the occurrence of random numbers simultaneously. In this study, the numbers a and m are set first. While the variable c obtained from random numbers generated in the previous stage. The result of this research is the computer-based test which applies for random numbers.

ON THE DISTRIBUTION OF NONLINEAR CONGRUENTIAL PSEUDORANDOM NUMBERS IN RESIDUE RINGS

The nonlinear congruential method is an attractive alternative to the classical linear congruential method for pseudorandom number generation. In this paper we present a new type of discrepancy bound for sequences of s-tuples of successive nonlinear congruential pseudorandom numbers over a ring of integers ℤM.