pseudo-random number generation for synthetic orderbook generation is highly important, the capability of picking a particular probability distribution, input the respective parameters, and generate the desired samples, is an general process required for scientific computations.
Problem
v0.0.4 doesn't has any probabilistic generator, so no random samples from a random distribution could be created.
Solution
create a module that has a list of available Probability Density Functions (PDF) to sample from, expose such functionality to other modules in the project.
Success Criteria
in examples/ create one example for, at least, the Poisson and Exponential distributions.
Enable, in another linked ticket, the creation of a quantitative model for the arrival time of a market order, and, the count of arrived orders given a period of time.
Context
pseudo-random number generation for synthetic orderbook generation is highly important, the capability of picking a particular probability distribution, input the respective parameters, and generate the desired samples, is an general process required for scientific computations.
Problem
v0.0.4 doesn't has any probabilistic generator, so no random samples from a random distribution could be created.
Solution
create a module that has a list of available Probability Density Functions (PDF) to sample from, expose such functionality to other modules in the project.
Success Criteria
examples/create one example for, at least, thePoissonandExponentialdistributions.