Questions tagged [julia]

Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments.

Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments, such as Ruby, Python, R or Matlab. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. The library, mostly written in Julia itself, also integrates mature, best-of-breed C and Fortran libraries for linear algebra, as well as highly proficient random number generation, FFTs, and string processing.

More libraries continue to be added over time. Programs written in Julia are organized around defining and overloading functions with different combinations of argument types. Part of what makes Julia so expressive is that argument types are user-defined.

The core of Julia is implemented in C and C++ and its parser in Scheme ("femtolisp"). For just-in-time generation of 64-bit or 32-bit optimized machine code the LLVM compiler framework is used depending on platform or user override.

The C API enables Julia with the capability of being called from C without needing to copy data.

Julia is based on LLVM and compares in speed with C and Fortran, while having syntax similar to MATLAB and R. Although it is still in its infancy, it is maturing quickly.

Resources for Julia:

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Does Julia have any hope of sticking in the statistical community?

I recently read a post from R-Bloggers, that linked to this blog post from John Myles White about a new language called Julia. Julia takes advantage of a just-in-time compiler that gives it wicked fast run times and puts it on the same order of…
Christopher Aden
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Julia: Taking stock of how it has been doing

I came across a 2012 question that had a very good discussion about Julia as an alternative to R / Python for various types of Statistical Work. Here lies the original Question from 2012 about Julia's promise Unfortunately Julia was very new back…
curious_cat
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QQ-Plots in Julia via Plots.jl?

I am trying to make QQ-Plots in Julia, but the only solution I could find is this old example using Gadfly. Given that it's being deprecated, I wanted to know if anyone knew of a solution for making the QQ-plots in Plots.jl. Maybe there's a stats…
Chris Rackauckas
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Explaining the numbers in a decision tree

Using the famous Iris data set with Julia decision tree classifier I get the following tree. using RDatasets using DecisionTree iris = dataset("datasets", "iris") features = convert(Array, iris[:, 1:4]) labels = convert(Array, iris[:, 5]); model =…
Istvan
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JuliaOpt Empirical Likelihood Estimation

I am trying to perform an empirical likelihood estimation in a regression setting using JuliaOpt (Convex or JuMP) and ran into difficulties using either API. The problem: Empirical likelihood for regression can be written as a maximization problem…
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Non-Linear Least Squares Sine Frequency Estimation in julia

I am trying to estimate an artificial non-linear maximum likelihood problem which works fine as long as there is no frequency in a sine function to estimate. I am using julia Optim and Distributions for this example, here is the code: function ml( …
Vincent
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mathematical difference between two functions used in scaling data and viewing distribution

I am trying to understand the difference between f(x) and g(x) below. I am not a mathematician or statistician, so please bear with me. Basically, I'm trying to specifically understand: what g is doing to the data what motivation, if any, there is…
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Large Sample Properties Least Square Estimator

I am trying to understand the properties of the least squares estimator. In particular the Gauss-Markov theorem states that the estimator is independent from the distribution of the error term. Thus if I understand correctly, the following should…
Vincent
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Agent based modeling: binding 2 agents together to form a H2 molecule in NetLogo (or Agents.jl)?

Note: I got the message: This question appears to be off-topic because it is not about probability, statistics, machine learning, data analysis, data mining, or data visualization. Agent based modeling is used to generate statistical data for…
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Find first Principal Component (and loading) using a fast iterative algorithm without covariance matrix

I have a matrix $X$ and I would like to find its first principal component and the corresponding loadings. I would like to do this without computing the covariance matrix of $X$. How can I do so? This is the standard version, which uses the…
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Bias in unbiased pseudo-marginal estimation?

In the Pseudo-marginal Metropolis-Hastings algorithm exact sampling of a posterior distribution is performed when using an unbiased estimate of the marginal likelihood. However, I am having problems with the unbiasedness of the marginal…
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proposal value between the generated data and the accepted previous proposal

I have a question here that has been confusing me these two days. So in mcmc hasting metropolis if a proposal value was accepted which means tha it's going to be the current value after that current=proposal, then we generate another proposal after…
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Coordinate Descent in Ordinary Least Squares not converging

As a warm-up to writing my own elastic net solver, I'm trying to get a fast enough version of ordinary least squares implemented using coordinate descent. So if $b = Ax$, I want to find $x$ that minimizes $$ \left\Vert b - Ax \right\Vert^2 $$ If…
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Unexpectedly slow convergence when classifying MNIST digits with a Neural Network

I recently finished my implementation of a multilayer artificial neural network in Julia; I train it with SGD (no momentum, no decay, no regularization, just basic SGD), computing the gradient by means of backpropagation. The weights and biases are…
dsans
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How to formulate probability P(X) into a logistic regression?

This might be quite basic but I'm struggling. I'm trying to take a published ecological model and implement it in the Turing.jl package using Julia. Say I have a number of species, $S$, and I want to find out the probability of any of them eating…
colebrookson
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