When the components are correlated however, generating them is much more difficult. The UncorrelatedRandomVectorGenerator class simplifies this process by setting the mean and deviation of each component once and generating complete vectors. When the components of these vectors are uncorrelated, they may be generated simply one at a time and packed together in the vector. Some algorithms require random vectors instead of random scalars. For example, to get a random value following a normal (Gaussian) distribution with mean 3 and standard deviation 1.5, you can use
The nextXxx methods allow you to get random deviates directly, without instantiating distributions. The javadoc for the nextXxx methods in RandomDataGenerator describes the algorithms used to generate random deviates. Hipparchus supports generating random sequences from each of the distributions in the distributions package. The mathematical concept of a probability distribution basically amounts to asserting that different ranges in the set of possible values of a random variable have different probabilities of containing the value. When using the built-in JDK function Math.random(), sequences of values generated follow the Uniform Distribution, which means that the values are evenly spread over the interval between 0 and 1, with no sub-interval having a greater probability of containing generated values than any other interval of the same length. There is no such thing as a single “random number.” What can be generated are sequences of numbers that appear to be random. Random sequence of numbers from a probability distribution The only modification required to the examples to use alternative PRNGs is to replace the argumentless constructor calls with invocations including a RandomGenerator instance as a parameter. The examples all use the default JDK-supplied PRNG.
#RANDOM DATA GENERATOR HOW TO#
Sections 2.2-2.6 below show how to use the Hipparchus API to generate different kinds of random data. Other good PRNGs suitable for Monte-Carlo analysis (but not for cryptography) provided by the library in the raondom. Whenever a default is provided, the javadoc indicates what the default is. In most cases, the default is a Well generator. The source of random data used by the data generation utilities is pluggable.
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