Julia Language is the hipster among all programming language. However, Julia is not only modish and fashionable, but also comes with a huge potential. If you wish to learn more about the Julia and its pros and cons, read the following post: Why use Julia Language!
In order to facilitate the start with Julia Language, I prepared a set of posts that contain the most important functionalities in Julia. Furthermore, I compared them to their counterpart in R.
The first post explains how to create a vector in Julia. It shows how to construct a row and a column vector. It also shows how to construct a vector that contains integers from j to n in k steps. The post further explains how to create a linearly spaced vector of k points.
The second post covers matrices. The post explains how one can create and fill a matrix. It further demonstrates how one can use simple Julia commands to create a matrix filled with zeros or ones. Finally, the post also shows how to create an identify matrix in Julia and how one can set up a diagonal matrix in Julia.
The third post demonstrates how to access elements within a vector or a matrix. It shows how to access specific elements, rows and columns within a matrix. Additionally, the post explains how to add and remove rows of a matrix, how to get the diagonal of a matrix and how to display the dimensions of a matrix.
In an additional post I included several examples of how to manipulate vectors and matrices in Julia. Among others, the post presents instructions of how to transpose a matrix, how to concatenate matrices horizontally and vertically and how to reshape a matrix. Furthermore, I show how to flip a matrix upside and down and from left to right and how to repeat a matrix several times.
This post summarizes the most important mathematical operations in Julia. It shows how to compute the Dot Product, conduct matrix multiplication, element-wise multiplication or how to calculate the power of a matrix in Julia. Furthermore, it explains how to calculate the inverse of a matrix, the determinant, Eigenvalues or Eigenvectors of a matrix in Julia.
Creating random is central to every programming language and statistical software. This post explains how to create random numbers in Julia. It explains how to create random numbers that a uniformly distributed and how to create random numbers that are normally distributed with mean zero and standard deviation one. It further explains how to create random number that are normally distributed, but have mean and standard deviation different from zero and one. Finally, the post also explains how to simulate random numbers that follow other distributions including a Gamma and Beta distribution.