Category: R

Feed: R-bloggers. Author: kjytay. The glmnet function (from the package of the same name) is probably the most used function for fitting the elastic net model in R. (It also fits the lasso and ridge regression, since they are special cases of elastic net.) The glmnet function is very powerful and has several function options that users may not know about. In a series of posts, I hope to shed some light on what these options do. Here is the full signature of the glmnet function: glmnet(x, y, family=c("gaussian","binomial","poisson","multinomial","cox","mgaussian"), weights, offset=NULL, alpha = 1, nlambda = 100, lambda.min.ratio = ifelse(nobsIn ... Read More

Feed: R-bloggers. Author: rOpenSci - open tools for open science. Antarctic/Southern Ocean science and rOpenSci Collaboration and reproducibility are fundamental to Antarctic and Southern Ocean science, and the value of data to Antarctic science has long been promoted. The Antarctic Treaty (which came into force in 1961) included the provision that scientific observations and results from Antarctica should be openly shared. The high cost and difficulty of acquisition means that data tend to be re-used for different studies once collected. Related R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R ... Read More

Feed: R-bloggers. Author: Hugo Bowne-Anderson. Hugo Bowne-Anderson, the host of DataFramed, the DataCamp podcast, recently interviewed Angela Bassa, the Director of Data Science at iRobot. Here is the podcast link. Hugo: Hi there Angela, and welcome to DataFramed. Angela: Thanks, thanks for having me. Hugo: It’s a great pleasure to have you on the show, and I’m really excited to be talking about managing data science teams today, and your work at iRobot. But, before we get into this conversation, I’d love to find out a bit about you. I thought maybe you could start by telling us what you’re ... Read More

Feed: R-bloggers. Author: Brian Lee Yung Rowe. I’m pleased to share Part I of my new book “Introduction to Reproducible Science in R“. The purpose of this book is to approach model development and software development holistically to help make science and research more reproducible. The need for such a book arose from observing some of the challenges that I’ve seen teaching graduate courses in natural language processing and machine learning, as well as training my own staff to become effective data scientists. While quantitative reasoning and mathematics are important, often I found that the primary obstacle to good data ... Read More

Feed: R-bloggers. Author: ntguardian. Introduction Over the past few weeks I’ve published articles about my new package, MCHT, starting with an introduction, a further technical discussion, demonstrating maximized Monte Carlo (MMC) hypothesis testing, bootstrap hypothesis testing, and last week I showed how to handle multi-sample and multivariate data. This is the final article where I explain the capabilities of the package. I show how MCHT can handle time series data. I should mention that I’m not focused on the merits of the procedures I use as examples in these posts, and that’s going to be the case here. It’s possible ... Read More

Feed: R-bloggers. Author: John Mount. This note is about attempting to remove the bias brought in by using sample standard deviation estimates to estimate an unknown true standard deviation of a population. We establish there is a bias, concentrate on why it is not important to remove it for reasonable sized samples, and (despite that) give a very complete bias management solution. Everitt’s The Cambridge Dictionary of Statistics 2nd Edition, Cambridge University Press defines a “statistic” as: A numeric characteristic of a sample. Informally we can say a statistic is a summary. And this lets us say the field of ... Read More

Feed: R-bloggers. Author: Ignacio Sarmiento Barbieri. This blog post introduces the RATest package we released a while back on CRAN with my colleague and good friend Mauricio Olivares-Gonzalez. The package contains a collection of randomization tests, data sets and examples. The current version focuses on two testing problems and their implementation in empirical work, mostly related to economics. First, it facilitates the empirical researcher to test for particular hypotheses, such as comparisons of means, medians, and variances from k populations using robust permutation tests, which asymptotic validity holds under very weak assumptions, while retaining the exact rejection probability in finite ... Read More

Feed: R-bloggers. Author: business-science.io - Articles. There are only two more weeks in the course! This week will extend what you learned from the Expected Value by performing an optimization and sensitivity analysis. The optimization and sensitivity analysis will teach you how to identify the maximum business savings for the overtime problem and see how additional factors change the amount of savings: Threshold Optimization – A method used to maximize expected saving via iteratively calculating savings at various thresholds Sensitivity Analysis – A method used to investigate how sensitive the expected savings is to various parameter values that were created ... Read More

Feed: R-bloggers. Author: Thinking inside the box. A new RcppArmadillo release, now at 0.9.200.4.0, based on the new Armadillo release 9.200.4 from earlier this week, is now on CRAN, and should get to Debian very soon. Armadillo is a powerful and expressive C++ template library for linear algebra aiming towards a good balance between speed and ease of use with a syntax deliberately close to a Matlab. RcppArmadillo integrates this library with the R environment and language–and is widely used by (currently) 532 (or 31 more since just the last release!) other packages on CRAN. This release once again brings ... Read More

Feed: R-bloggers. Author: Michael Griebe. Week 10 Gold Mining and Fantasy Football Projection Roundup now available. Go get that free agent gold! The post Gold-Mining Week 10 (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, or facebook ... Read More