Handy Guide to Linear Congruential Method for Random Number Generation

Jul 04, 2025

70 likes | 177 Vues

Learn how to generate random numbers with the Linear Congruential Method in Excel using given parameters X0, a, m, and c. This guide provides step-by-step instructions and examples for creating random integers efficiently.

Share Presentation

Embed Code

bruno-solomon

Télécharger la présentation

Handy Guide to Linear Congruential Method for Random Number Generation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Random Number Generation • Linear Congruential Method X0, a, m and c are given • Random integer: Xi+1=(aXi+c) mod m • Random number: Ri= Xi+1/m Example:In excel generate 100 random number with given parameters

Random Number Generation

Random Number Generation. Pseudo-random number Generating Discrete R.V. Generating Continuous R.V. Pseudo-random numbers. Almost random numbers ! Actually, they are “computer-generated random numbers.”

614 views • 28 slides

Random Number Generation

Random Number Generation. Concern with generating random numbers that have the following conditions: Uniformity Independence Efficiency Replicability Long Cycle Length. Random Number Generation (cont.).

500 views • 22 slides

Pseudo-random Number Generation

Pseudo-random Number Generation . Qiuliang Tang. Random Numbers in Cryptography . The keystream in the one-time pad The secret key in the DES encryption The prime numbers p, q in the RSA encryption The private key in DSA The initialization vectors (IVs) used in ciphers.

1.31k views • 31 slides

Random Number Generation

Random Number Generation. Plan: Introduce basics of RN generation Define concepts and terminology Introduce RNG methods Linear Congruential Generator (LCG) Explicit Inversive Congruential Generator Non-linear Additive Feedback Transform-Expand-Sample (TES) Technical issues for RNGs

434 views • 14 slides

Random Number Generation

Random Number Generation. Desirable Attributes: Uniformity Independence Efficiency Replicability Long Cycle Length. Random Number Generation (cont.).

552 views • 33 slides

Random Number Generation

Random Number Generation. Section 3.10 Section 4.12. Outline. Observations from the last week’s lab Anatomy of a Verilog Program More about Verilog Including a file Test a Module with a Random Sequence Example: NAND Implementation of a NOT Gate The NAND Implementation of a NOR Gate

502 views • 36 slides

Random Number Generation

Random Number Generation. Graham Netherton Logan Stelly. What is RNG?. RNG = Random Number Generation Random Number Generators simulate random outputs, such as dice rolls or coin tosses. Traits of random numbers. Random numbers should have a uniform distribution across a range of values

585 views • 26 slides

Pseudo-Random Number Generation

Pseudo-Random Number Generation. CSIS 5857: Encoding and Encryption. Random Number Generation. Crucial to key generation Crucial to many other applications (games, etc.) Desired properties: 1 or 0 equally likely to be generated

627 views • 13 slides

UNIFORM RANDOM NUMBER GENERATION

UNIFORM RANDOM NUMBER GENERATION. The goal is to generate a sequence of Uniformly distributed Independent X 1 , X 2 , …. IID Unif[0, 1] These are the basis of generating all random variates in simulations. UNIFORM [0,1]. f(x). Every real number beteween 0 and 1 is equally likely…. 1.

417 views • 16 slides

Random Number and Random Variate Generation

Random Number and Random Variate Generation. Random Number and Random Variate Generation. How does the computer generate observations from various distributions specified after input analysis? There are two main components to the generation of observations from probability distributions.

871 views • 45 slides

Random-Number Generation

Random-Number Generation. Andy Wang CIS 5930-03 Computer Systems Performance Analysis. Generate Random Values. Two steps Random-number generation Get a sequence of random numbers distributed uniformly between 0 and 1 Random- variate generation

858 views • 43 slides

Parallel Random Number Generation

Parallel Random Number Generation. Ashok Srinivasan Florida State University asriniva@cs.fsu.edu. If random numbers were really random, then parallelization would not make any difference … and this talk would be unnecessary

538 views • 30 slides

Random-Number Generation

Random-Number Generation. Raj Jain Washington University Saint Louis, MO 63130 Jain@cse.wustl.edu Audio/Video recordings of this lecture are available at: http://www.cse.wustl.edu/~jain/cse574-08/. Overview. Desired properties of a good generator Linear-congruential generators

694 views • 46 slides

Random Number Generation

Random Number Generation. Dates Setting up Random Dates is a simple process using the Date function. = Randbetween ( StartDate,EndDate ) Dates in a Range of Years

233 views • 4 slides

PARALLEL RANDOM NUMBER GENERATION

PARALLEL RANDOM NUMBER GENERATION. Ahmet Duran CISC 879. Outline. Random Numbers Why To Prefer Pseudo- Random Numbers Application Areas The Linear Congruential Generators Period of Linear Congruential Sequence Approaches to the Generation of Random Numbers on Parallel Computers

498 views • 37 slides

Random-Number Generation

Random-Number Generation. Overview. Desired properties of a good generator Linear-congruential generators Tausworthe generators Survey of random number generators Seed selection Myths about random number generation. Random-Number Generation. Random Number = Uniform (0, 1)

1.01k views • 46 slides

Chapter 7 Random-Number Generation

Chapter 7 Random-Number Generation. Banks, Carson, Nelson & Nicol Discrete-Event System Simulation. Purpose & Overview. Discuss the generation of random numbers. Introduce the subsequent testing for randomness: Frequency test Autocorrelation test. Properties of Random Numbers.

1.08k views • 23 slides

Random-Number Generation

Random-Number Generation. Properties of Random Numbers. Random Number, R i , must be independently drawn from a uniform distribution with pdf: Two important statistical properties: Uniformity Independence. U(0,1). Figure: pdf for random numbers. Generation of Pseudo-Random Numbers.

508 views • 28 slides

Part 6: Random Number Generation

Part 6: Random Number Generation. Agenda. Properties of Random Numbers Generation of Pseudo-Random Numbers (PRN) Techniques for Generating Random Numbers Tests for Random Numbers Caution. 1. Properties of Random Numbers (1).

967 views • 42 slides

Random Number Generation Fall 2012

Random Number Generation Fall 2012. By Yaohang Li, Ph.D. Review. Last Class Variance Reduction This Class Random Number Generation Uniform Distribution Non-uniform Distribution Random Number Generation Assignment 3 Next Class Quasi-Monte Carlo. Random Numbers.

669 views • 32 slides

Random Number Generation

Random Number Generation. Pseudo-Random Generation. rand(). #include < iostream > using namespace std; int main() { for( int i = 1; i <= 10; i ++) cout << rand() << endl ; return 0; }. rand(). First Execution.

215 views • 10 slides

Random Number Generation

Random Number Generation. Random Number Generators. Without random numbers, we cannot do Stochastic Simulation Most computer languages have a subroutine, object or function generating random numbers (uniformly distributed)

629 views • 17 slides

More Related