Category: R

Feed: R-bloggers. Author: R-bloggers | A Random Walk. Automatic differentiation in R with Stan Math | R-bloggers .grad[, "A"] .grad[, "lam"] .grad[, "b"] attr(.value, "gradient") .value #> } Since we specified the function.arg argument, deriv() returns a function –instead of an expression– that can be used directly to evaluate both the function values and the gradient (or Jacobian) for different values of the independent variable and parameters. Inspecting the body of the returned function, we see that the expression in the "gradient" attribute corresponds exactly to the manually derived gradient. ## evaluate function + jacobian fdot(x = (1:10) / 10, ... Read More

Feed: R-bloggers. Author: R | JLaw's R Blog. Normally, I would do some EDA to better understand the data set but in the interest of word count I’ll jump right into using tidymodels to predict whether or not a given field goal attempt will be iced. In order to make the data work with the XGBoost algorithm I’ll subset and convert some numeric variables including our dependent variable to factors. A frustrating thing I learned in writing this post is that with a factor dependent variable the assumption is that the first level is the positive class. I’m recoding is_iced ... Read More

Feed: R-bloggers. Author: R Views. [This article was first published on R Views, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. One hundred thirty-four new packages made it to CRAN last December. Here are my “Top 40” picks in eight categories: Data, Genomics, Machine Learning, Medicine, Science, Statistics, Utilities, and Visualization. Data aurin v0.5.1: Implements an API for AURIN, Australia’s largest resource for accessing clean, integrated, spatially enabled and research-ready data on issues ... Read More

Feed: R-bloggers. Author: Bob Muenchen. [This article was first published on R | r4stats.com, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. by Robert A. Muenchen Introduction R-Instat is a free and open source graphical user interface for the R software that focuses on people who want to point-and-click their way through data science analyses. Written in Visual Basic, it is currently only available for Microsoft Windows. However, a Linux version is in development using ... Read More

Feed: R-bloggers. Author: Ronan Harrington. Setup Loading the R libraries and data set. # Loading libraries library(geomtextpath) # For adding text to ggplot2 curves library(tidytuesdayR) # For loading data set library(ggbeeswarm) # For creating a beeswarm plot library(tidyverse) # For the ggplot2, dplyr libraries library(gganimate) # For plot animation library(ggthemes) # For more ggplot2 themes library(viridis) # For plot themes # Loading data set tt <- tt_load("2022-01-11") Downloading file 1 of 2: `colony.csv` Downloading file 2 of 2: `stressor.csv` Data wrangling In this section, the Bee Colony data is wrangled into two tidy sets: tidied_colony_counts_overall contains quarterly colony counts for ... Read More

Feed: R-bloggers. Author: Ivan Svetunkov. [This article was first published on R – Open Forecasting, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. At the end of June 2021, I released the greybox package version 1.0.0. This was a major release, introducing new functionality, but I did not have time to write a separate post about it because of the teaching and lack of free time. Finally, Christmas has arrived, and I could ... Read More

Feed: R-bloggers. Author: Posts &#124; Joshua Cook. [This article was first published on Posts | Joshua Cook, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. In chapter 17 “Parametric nonlinear models” of Bayesian Data Analysis by Gelman et al., the authors present an example of fitting a curve to a serial dilution standard curve and using it to estimate unknown concentrations. Below, I build the model with Stan and fit it using MCMC ... Read More

Feed: R-bloggers. Author: Avi. For my handful of followers, you may have noticed something strange. Over the past two days, I released updates to all four of my packages on CRAN. I decided to practice what I preach and actively reduce dependency hell by moving from testhat to tinytest. I have been programming for over 20 years, and continue to realize that reducing dependencies is worth the extra effort for both programmer and end-user. Even though it may require extra work up-front, having fewer dependencies which can seriously impact your own projects’ stability is worth it. This is one of ... Read More

Feed: R-bloggers. Author: Boris Guarisma. [This article was first published on Foundations, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Cover photo by Markus Spiske on Unsplash Go to R-bloggers for R news and tutorials contributed by hundreds of R bloggers. Introduction This is the sixth of a series of 6 articles about time series forecasting with panel data and ensemble stacking with R. Through these articles I will be putting into practice ... Read More

Feed: R-bloggers. Author: Boris Guarisma. [This article was first published on Foundations, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Cover photo by Hannah Busing on Unsplash Go to R-bloggers for R news and tutorials contributed by hundreds of R bloggers. Introduction This is the fifth of a series of 6 articles about time series forecasting with panel data and ensemble stacking with R. Through these articles I will be putting into practice ... Read More