Contents
Can a random seed be negative?
No. For a good quality RNG, the choice of seed will not affect the quality of the output. A set of seeds [1,2,3,4,5,6,7,8,9,10] should result in the same quality of randomness as any random selection of 10 ints.
What are the problems that occur while generating pseudo random numbers?
Lack of uniformity of distribution for large quantities of generated numbers; Correlation of successive values; Poor dimensional distribution of the output sequence; Distances between where certain values occur are distributed differently from those in a random sequence distribution.
Why do we need pseudo-random number generators?
Applications of PRNG PRNGs are suitable for applications where many random numbers are required and where it is useful that the same sequence can be replayed easily. Popular examples of such applications are simulation and modeling applications.
Can a pseudorandom number be a random number?
The pseudorandom numbers you obtain will be nothing more than the seeds you run through a mathematical function. The results you obtain will not pass for random unless the seeds you choose pass for random.
Why do you use the same seed number for all random numbers?
The seed number you choose is the starting point used in the generation of a sequence of random numbers, which is why (provided you use the same pseudo-random number generator) you’ll obtain the same results given the same seed number.
Why is it a bad idea to set the seed?
To see why this is such a bad idea, consider the limiting case: You set the seed, draw one pseudorandom number, reset the seed, draw again, and so continue. The pseudorandom numbers you obtain will be nothing more than the seeds you run through a mathematical function.
What’s the argument of set.seed in R?
If mathematically you require a number of pseudo-randomly-generated numbers, then there can’t be a pattern to the numbers you choose. The set.seed ()function in R takes an (arbitrary) integer argument. So we can take any argument, say, 1 or 123 or 300 or 12345 to get the reproducible random numbers.