Julia is a high-level, high-performance programming language specifically designed for numerical and scientific computing. It is gaining popularity among data scientists and researchers due to its speed and ease of use. In
When it comes to contributing to distributions in Julia, there are several ways to approach the problem. In this article, we will explore three different solutions, each with its own advantages and
When working with Julia, fitting a multivariate normal distribution to a matrix with distributions can be achieved in different ways. In this article, we will explore three different options to solve this
When working with mixture models in Julia, it is important to specify the weights for each component in the mixture. In this article, we will explore three different ways to specify the
