The Beginner’s Guide to R Profiler: Profiler is a tool in R that helps you to identify performance bottlenecks in your code by measuring the execution time of each function and line of code. The profiler generates a report that shows you which functions or lines of code are taking the most time to execute, allowing you to optimize your code for faster performance. system.time() Before we start talking about functions in R that are used for profiling your code, i wanted to talk about system.time() function . So, the system.time() function is another tool in R that you can use to measure the execution time of your code. It works by running your code and returning the amount of time it took to run in seconds. Here's an example of how to use it: # Run your code and measure the execution time system.time({ # Your code here }) While system.time() can be useful for quickly measuring the execution time of small code snippets, it has some limitations compared to the profiler. Here are a...
The Beginner’s Guide to Simulation in R: Simulation is the process of generating artificial data based on a set of assumptions or models. R programming provides a variety of functions and packages for simulating different types of data. In this blog post, we will cover the basics of simulation in R programming, including the most commonly used functions, distributions, and simulations using linear models. Functions for Simulation in R R programming provides various functions for simulation, such as: runif() – used to simulate data from a uniform distribution rnorm() – used to simulate data from a normal distribution rexp() – used to simulate data from an exponential distribution rgamma() – used to simulate data from a gamma distribution rpois() – used to simulate data from a Poisson distribution rbeta() – used to simulate data from a beta distribution rbinom() – used to simulate data from a binomial distribution rcauchy() – used to simulate data from a Cauchy distribution Distributio...