- It is the global standard for data analysis and machine learning algorithms.
- It is interactive and easy to use once you're familiar with its command syntax. R functions are short and effective.
- It has ready-to-use extensions - "packages" - for all imaginable tasks, including support vector machines, genetic optimization, several kinds of neural networks, and deep learning algorithms.
- It is continuously developed and supported by the global scientific community. The time between the publication of an idea and its implementation in a R package is usually very short.
- It is free. As Linus Torvalds said: "Software is like sex - it's better when it's free".

R Bridge is an interface (but notice that not in the sense of an interface in object oriented programming) to the R language. You use Rset functions to pass values to R variables (in R variables can be created on the fly) and Rx to execute the R code passed as argument.

Is R Bridge like a whole different language which we get access to via the R Bridge?

For example - are one able to make a simple moving average crossover system with R Bridge?

Compared to the tools, for example spectral filters, that comes with Zorro - are the tools that comes with R Bridge completely different?

Unvectorized implementation:
double prediction = 0.0;
for (int j = 0; j < n; j++)
prediction += theta[j] * x[y];

Vectorized implementation:
double prediction
= theta.transpose() * x;

Will potential functions to Zorro be lessed focused on from now on?

Is the R language being used to code completely different strategies with different indicators than the ones that come with Zorro?

What can we do with R that we can't do with Zorro?

No problem, I myself coming from an IT background find it difficult to understand some concepts of Zorro. I will proceed to answer your questions in between quotes and later I add some more info, remember also that jcl said that they will set up an R bridge tutorial soon



Yes, R is an -interpreted- programming language like MatLab or Octave which is focused in scientific problems



Yes, you can do almost anything with R, with less work or more work than in other languages. I, for instance, would not implement a moving average crossover strategy in R since Zorro already provides a simple way to do it. Unless I want to do something very specific with the moving average strategy that Zorro can't...



As said before you can do almost anything with any programming language, the thing with R is that it has a lots of packages ie libraries developed that tackle lots of problems like machine learning and also it brings native support to efficiently perform operations on data like vectors, for instance if you want to multiply the vectors theta and x in Octave (it's the same in R):



The Vectorized implementation is more efficient. I took that from this course which I did and recommend , there is going to be another edition soon.





This I don't know. Will leave that to jcl and the Zorro team. But I hope Zorro functions are still maintained and more functions to develop strategies free of bias are added.



Well, as said before, R is more appropriate ie less time consuming to develop strategies which use machine learning algorithms.



An example would be using a neural network with a hidden layer of more than one neuron. You would use one neural network package of R (or even from a dll of the C/C++ language like dlib, libSVM and many more:
)
and call it in adviseLong/Short using NEURAL method.

In Zorro as of today, you can only use a PERCEPTRON which is a neural network with only one neuron. (And as I recall, jcl told me in a post that it is trained without using gradient descent so inputs don't need to be normalized).

Here is some more explanation: You can code anything you want in any language, export it to a dll and call it from Zorro. Problem is, it is rather difficult/time consuming to do all the coding your own. As said before R is a language with a large community of developers of machine learning and statistics packages. Check for instance these links:



And this one for another course in programming with R:



Feel free to ask if there is something that you don't understand. I also am looking forward for a tutorial or example of an strategy using the R bridge.