https://www.thefinalartefact.xyz/tags/functional/Recent content in Functional on The Final ArtefactHugoen-gbThu, 09 Dec 2021 00:00:00 +0000https://www.thefinalartefact.xyz/post/beauty-of-r-and-big-o/Thu, 09 Dec 2021 00:00:00 +0000https://www.thefinalartefact.xyz/post/beauty-of-r-and-big-o/<script src="index_files/kePrint/kePrint.js"></script> <link href="index_files/lightable/lightable.css" rel="stylesheet" /> <h2 id="big-o">Big-O</h2> <p>The purpose of this is not to provide yet another primer on the Big-O/$\Omega$/$\Theta$ notation but to share my enduring appreciation for working with R. I will introduce Big-O only briefly to provide context but I would refer all of those who are interested to the linked materials.</p> <h2 id="what-is-big-sth-notation">What is Big-sth notation</h2> <p>When analysing functions, we may be interested in knowing how fast a function grows. For instance, for function <code>\(T(n)=4n^2-2n+2\)</code>, after ignoring constants, we would say that <code>\(T(n)\)</code> grows at the order of <code>\(n^2\)</code>. With respect to the <em>Big-O</em> notation we would write <code>\(T(n)=O(n^2)\)</code>^[MIT. (2021, December 9). Big O notation. Introduction to Computers and Programming. Retrieved December 26, 2021, from <a href="https://web.mit.edu/16.070/www/lecture/big_o.pdf">https://web.mit.edu/16.070/www/lecture/big_o.pdf</a>]. Most commonly, in computer science, we would differentiate between Big O, Big Theta <code>\((\Theta)\)</code> and Big Omega <code>\((\Omega)\)</code>. In a nutshell, the differences between those common notations can be summarised as follows:</p>