![]() So I will for the moment assume that what I am doing is ok and perhaps in the future use randjump() to ensure unique streams as suggested by rfourquet. The codes generated is available as a downloadable CSV file where you can import them into your database or application, or mail merge them to print onto. RNGs find applications in various fields, including computer simulations, cryptography, and gaming, where true randomness is essential. From some very naive testing it doesn't seem like there is an obvious problem, for example if I take seeds 1:10000 in Julia and look at the distribution of the initial random numbers is appears uniformly distributed, and if I take the first ten thousand random numbers from each stream (what I'm doing in my MC simulations) and test for repeated values between the streams (using the function unique(), probably some better tests out there?) I only get 1 repeated value out of 10^8. A random number generator (RNG) is a computational tool or algorithm that generates a sequence of numbers that appear random and lack any predictable pattern. Step 4: If you are happy with the randomly selected numbers, you can pick a number or copy the results directly to your clipboard, share. Step 3: Submit the answers by clicking the green button to generate your list of random numbers instantly. It is of course true that any set of N fixed seeds can only produce N initial random numbers, the question is then whether taking seeds as 1:N gives a representative random distribution on [0,1) for this first value and whether there is any overlap in the following streams. Step 2: Choose the number of columns you want the true random number sequence generator to display. I think I understand the problem now better, thanks to your answers and the discussion in the issue filed above. So I would like to know if there is a problem with seeding Julia's random number generator in this way? Will it bias my sample or does Julia somehow avoid this in the way it processes the seed given to srand()? And finally, if it is a bad idea, what would be the best way to seed so that I can reproduce everything at a later stage? Start Random Generator Generate random integers Create random real numbers in Excel Fill the range with dates at. However, I recently saw that at least in C++ ( ), seeding the Mersenne Twister with integers like this is a bad idea. My primary motivation for this is that I would like to reproduce a particular run if I see anything strange. Enter a value in each of the first three text boxes. For help in using the Random Number Generator, read the Frequently-Asked Questions. Naively I have set the seed specifically for each run of the code as the integer corresponding to the run, i.e., I run the code starting with srand(1), srand(2), etc. Use the Random Number Generator to create a list of random numbers (up to 10,000 numbers), based on your specifications. I am doing Monte Carlo simulations using Julia, where I have some code that depends on the output from the rand() function and then I run this code with many different initial seeds. RANDOM.ORG offers true random numbers to anyone on the Internet. I have a question about how Julia handles the seed given to the random number generator through the function srand(seed).
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