New article Statistical Distributions in MQL5 - taking the best of R has been published:
The R language is one of the best tools of statistical processing and analysis of data. Thanks to availability and support of multiple statistical
distributions, it had become widespread in the analysis and processing
of various data. Using the apparatus of probability theory and
mathematical statistics allows for a fresh look at the financial market
data and provides new opportunities to create trading strategies. With
the statistical library, all these features are now available in the
Let us consider the functions for working with the basic statistical distributions implemented in the R language.
Those include the Cauchy, Weibull, normal, log-normal, logistic,
exponential, uniform, gamma distributions, the central and noncentral
beta, chi-squared, Fisher's F-distribution, Student's t-distribution, as
well as the discrete binomial and negative binomial distributions,
geometric, hypergeometric and Poisson distributions. In addition, there
are functions for calculating theoretical moments of distributions,
which allow to evaluate the degree of conformity of the real
distribution to the modeled one.
The MQL5 standard library has been supplemented with numerous
mathematical functions from R. Moreover, an increase in operation speed
of 3 to 7 times has been achieved, compared to the initial versions in
the R language. At the same time, errors in implementation of certain
functions in R have been found.
Fig. 2. Distribution
histogram of random numbers, generated according to the normal
distribution with the parameters mu=5 and sigma=1
Author: MetaQuotes Software Corp.