Tag: regression

Feed: R-bloggers. Author: arthur charpentier. Some pre-Halloween post today. It started actually while I was in Barcelona : kids wanted to go back to some store we’ve seen the first day, in the gothic part, and I could not remember where it was. And I said to myself that would be quite long to do all the street of the neighborhood. And I discovered that it was actually an old problem. In 1962, Meigu Guan was interested in a postman delivering mail to a number of streets such that the total distance walked by the postman was as short as ... Read More

Feed: R-bloggers. Author: R on Gianluca Baio. I have just submitted a revised version of survHE on CRAN — it should be up very shortly. This will be version 1.0.64 and its main feature is a major restructuring in the way the rstan/HMC stuff works. Basically, this is due to a change in the default C++ compiler. I don’t think much will change in terms of how survHE works when running full Bayesian models using HMC, but R now compiles it without problems. After the advice of Ben Goodrich, I have also modified the package so that it compiles the ... Read More

Feed: R-bloggers. Author: Kristian Larsen. Categories Visualizing Data Tags Data Visualisation ggplot2 R Programming tidyverse Visualization is a great way to get an overview of credit modeling. Typically you will start by making data management and data cleaning and after this, your credit modeling analysis will start with visualizations. This article is, therefore, the first part of a credit machine learning analysis with visualizations. The second part of the analysis will typically use logistic regression and ROC curves. Library of R packages In the following section we will use R for visualization of credit modelling. First we read the packages ... Read More

Feed: R-bloggers. Author: ThisIs Stats. In 2016, 2.1 million Americans were found to have an opioid use disorder (according to SAMHSA), with drug overdose now the leading cause of injury and death in the United States. But some of the country’s top minds are working to fight this epidemic, and statisticians are helping to lead the charge.  In This is Statistics’ second annual fall data challenge, high school and undergraduate students will use statistics to analyze data and develop recommendations to help address this important public health crisis.  The contest invites teams of two to five students to put their statistical and data visualization ... Read More

Feed: R-bloggers. Author: Michael Griebe. Week 7 Gold Mining and Fantasy Football Projection Roundup now available. Go check out our cheat sheet for this week. The post Gold-Mining Week 7 (2018) appeared first on Fantasy Football Analytics. Related R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more... If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, ... Read More

Feed: R-bloggers. Author: Ryan Sheehy. Here is the course link. Course Description Data visualization is an integral part of the data analysis process. This course will get you introduced to rbokeh: a visualization library for interactive web-based plots. You will learn how to use rbokeh layers and options to create effective visualizations that carry your message and emphasize your ideas. We will focus on the two main pieces of data visualization: wrangling data in the appropriate format as well as employing the appropriate visualization tools, charts and options from rbokeh. Chapter 1: rbokeh Introduction (Free) In this chapter we get ... Read More

Feed: R-bloggers. Author: Ryan Sheehy. Here is the course link. Course Description This course will help you take your data visualization skills beyond the basics and hone them into a powerful member of your data science toolkit. Over the lessons we will use two interesting open datasets to cover different types of data (proportions, point-data, single distributions, and multiple distributions) and discuss the pros and cons of the most common visualizations. In addition, we will cover some less common alternatives visualizations for the data types and how to tweak default ggplot settings to most efficiently and effectively get your message ... Read More

Feed: R-bloggers. Author: Marcelo S. Perlin. An Introduction to Loops in R – First, if you are new to programming, you should know that loops are away to tell the computer that you want to repeat some operation for anumber of times. This is a very common task that can be found in manyprogramming languages. For example, let’s say you invited five friendsfor dinner at your home and the whole cost of four pizzas will be splitevenly. Assume now that you must give instructions to a computer oncalculating how much each one will pay at the end of dinner. For ... Read More

Feed: R-bloggers. Author: RStudio Team. Continuing our series on new features in the RStudio v1.2 preview release, we would like to introduce shinytest. shinytest is a package to perform automated testing for Shiny apps, which allows us to: shinytest is available on CRAN, supported in RStudio v1.2 preview and can be installed as follows: install.packages("shinytest") Recording Tests This is the general procedure for recording tests: Run recordTest() to launch the app in a test recorder. Create the tests by interacting with the application and telling the recorder to snapshot the state at various points. Quit the test recorder. When you ... Read More

Feed: R-bloggers. Author: Kristian Larsen. Categories Data Management Tags Databases Import Data R Programming Tips & Tricks In this article, you learn how to connect R with Excel by importing and exporting data between the two programs. Excel: pros and cons Excel is still very popular among companies and organizations. One of the main advantages in a spreadsheet is ease of providing the user with a rapid overview of a dataset, using visualizations and tables. On the other hand, given the incredible growth of data, the spreadsheet really lacks efficient and agile solutions for data management and data cleaning. Solution: ... Read More