word2vec in R

[This article was first published on bnosac :: open analytical helpers – bnosac :: open analytical helpers, 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. ShareTweet Learn how … Read more word2vec in R

Tip (4), Variable Explorer for both R and Python in RStudio

In recent past, frequent usage of both Rand Python by Data Scientists are considerably increasing. RStudio is preferred IDE for most of R users, though, there are Editors and Notebooks which serve for both languages, yet, switching between them is not easy. Especially for those who got used to RStudio “Environment” tab for exploring objects in current R sessions; though, writing/execution of  Related Favorite

Open-Source Authorship of Data Science in Education Using R

[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. Joshua M. Rosenberg, Ph.D., is Assistant Professor of STEM Education at theUniversity … Read more Open-Source Authorship of Data Science in Education Using R

Announcing Public Package Manager and v1.1.6

[This article was first published on RStudio Blog, 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. Today we are excited to release version 1.1.6 of RStudio Package Manager … Read more Announcing Public Package Manager and v1.1.6

beta: Evidence-based Software Engineering – book

[This article was first published on The Shape of Code » R, 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. My book, Evidence-based software engineering: based on the … Read more beta: Evidence-based Software Engineering – book

Measuring Financial Risk: A Step-by-Step Guide

To calculate our own VaR and ES, we’ll use data for the Wilshire 5000, a stock market index widely considered to be the broadest measure of U.S. stock prices. We can use quantmod to import our data from FRED, the Federal Reserve Economic Database. We’ll also use ggplot2 to visualize our data. Let’s load our … Read more Measuring Financial Risk: A Step-by-Step Guide

Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models

Forecasting the future has always been one of man’s biggest desires and many approaches have been tried over the centuries. In this post we will look at a simple statistical method for time series analysis, called AR for Autoregressive Model. We will use this method to predict future sales data and will rebuild it to … Read more Time Series Analysis: Forecasting Sales Data with Autoregressive (AR) Models

The Bechdel test and the X-Mansion with tidymodels and #TidyTuesday

[This article was first published on rstats | Julia Silge, 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. Lately I’ve been publishingscreencasts demonstrating how to use thetidymodels framework, … Read more The Bechdel test and the X-Mansion with tidymodels and #TidyTuesday

Why R? Webinar – JD Long – Helping drive data science adoption in organizations

[This article was first published on http://r-addict.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. July 2nd (8:00pm UTC+2) is a date for the last Webinar at Why … Read more Why R? Webinar – JD Long – Helping drive data science adoption in organizations

one bridge further

[This article was first published on R – Xi’an’s Og, 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. Jackie Wong, Jon Forster (Warwick) and Peter Smith have just … Read more one bridge further

Neural Networks using Tensorflow via Keras in R – Video

[This article was first published on http://r-addict.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. On June 25th we had a pleasure to host Why R? Webinar with … Read more Neural Networks using Tensorflow via Keras in R – Video

Introducing Modeltime: Tidy Time Series Forecasting using Tidymodels

[This article was first published on business-science.io, 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. I’m beyond excited to introduce modeltime, a new time series forecasting package designed … Read more Introducing Modeltime: Tidy Time Series Forecasting using Tidymodels

Introduction to Factors in R

Factors play a crucial role in data analysis. Learn how to create, subset, and compare them. A factor refers to a statistical data type used to store categorical variables. Categorical variables belong to a limited number of categories. Continuous variables, on the other hand, can correspond to an infinite number of values. It is important … Read more Introduction to Factors in R

Reshape R dataframes wide-to-long with melt — tutorial and visualization

Before we begin our melt tutorial, let’s recreate the wide dataframe above. df_wide <- data.table(student = c(“Andy”, “Bernie”, “Cindey”, “Deb”),school = c(“Z”, “Y”, “Z”, “Y”),english = c(10, 100, 1000, 10000), # eng gradesmath = c(20, 200, 2000, 20000), # math gradesphysics = c(30, 300, 3000, 30000) # physics grades)df_wide student school english math physics1: Andy … Read more Reshape R dataframes wide-to-long with melt — tutorial and visualization

Simulating Spectroscopic Data Part 1

It is well-recognized that one of the virtues of the R language is the extensive tools it provides for working with distributions. Functions exist to generate random number draws, determine quantiles, and examine the probability density and cumulative distribution curves that describe each distribution. This toolbox gives one the ability to create simulated data sets … Read more Simulating Spectroscopic Data Part 1

Netflix vs Disney+. Who has more fresh titles?

[This article was first published on R-posts.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. “Let`s shift to Disney+”, said my wife desperately browsing Netflix on her phone. … Read more Netflix vs Disney+. Who has more fresh titles?

RcppSimdJson 0.0.6: New Upstream, New Features!

[This article was first published on Thinking inside the box , 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. A very exciting RcppSimdJson release with the updated upstream … Read more RcppSimdJson 0.0.6: New Upstream, New Features!

Flying Saucers and Bright Lights: A Data Visualization

[This article was first published on Deeply Trivial, 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. Earlier last week, I taught part 2 of a course on using … Read more Flying Saucers and Bright Lights: A Data Visualization

Speeding up your Continuous Integration Builds

[This article was first published on r – Jumping Rivers, 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. Continuous integration is an amazing tool when developing R packages. … Read more Speeding up your Continuous Integration Builds

Finding Economic Articles with Data (2nd Update)

Almost a year is now gone since I posted my last update about my shiny-powered search app. It allows to search among currently more than 5000 economic articles that have an accessible data and code supplement: https://ejd.econ.mathematik.uni-ulm.de The main data for my app can be downloaded as a zipped SQLite database from my server. Let … Read more Finding Economic Articles with Data (2nd Update)

How to Write Production-Ready R Code: Tools and Patterns

This talk was presented virtually at eRum 2020 and useR 2020 by Appsilon engineer Marcin Dubel. Here is a direct link to the video. Be Proud of Your Code! In this talk you’ll learn the tools and best practices for making clean, reproducible R code in a working environment ready to be shared and productionized. … Read more How to Write Production-Ready R Code: Tools and Patterns

The mr_uplift package in R: A Practitioners Guide to Trade-Offs in Uplift Models

The mr_uplift package in R: A Practitioners Guide to Trade-Offs in Uplift Models | R-bloggers [This article was first published on sweissblaug, 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 … Read more The mr_uplift package in R: A Practitioners Guide to Trade-Offs in Uplift Models

Pin package versions in your production Docker image

Using package in R is easy. You install from CRAN using install.packages(“packagename”), it resolves dependencies and you’re good to go. What R natively doesn’t handle so well is installing a particular package version without jumping through hoops. Technically you need the source file of the package version you want to install AND all source files … Read more Pin package versions in your production Docker image

Estimating Standard Errors for a Logistic Regression Model optimised with Optimx in R

[This article was first published on R | Joshua Entrop, 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 my last post I estimated the point estimates for … Read more Estimating Standard Errors for a Logistic Regression Model optimised with Optimx in R

Performance anxiety

In our last post, we took a quick look at building a portfolio based on the historical averages method for setting return expectations. Beginning in 1987, we used the first five years of monthly return data to simulate a thousand possible portfolio weights, found the average weights that met our risk-return criteria, and then tested … Read more Performance anxiety

Critique of “Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period” — Part 3: Estimating reproduction numbers

This is the third in a series of posts (previous posts: Part 1, Part 2) in which I look at the following paper: Kissler, Tedijanto, Goldstein, Grad, and Lipsitch, Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period, Science, vol. 368, pp. 860-868, 22 May 2020 (released online 14 April 2020).  The paper is also available … Read more Critique of “Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period” — Part 3: Estimating reproduction numbers

Fast.ai in R: How to Make a Computer Vision Model within an R Environment

This talk was presented virtually at eRum 2020 and useR 2020. Learn more about Appsilon‘s ML wildlife preservation project here. Yes, R programmers can make machine learning models, too! In this presentation, we will discuss using the latest techniques in computer vision as an important part of “AI for Good” efforts, namely, enhancing wildlife preservation. … Read more Fast.ai in R: How to Make a Computer Vision Model within an R Environment

Estimating Group Differences in Network Models using Moderation

[This article was first published on Jonas Haslbeck – r, 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. Researchers are often interested in comparing statistical network models across … Read more Estimating Group Differences in Network Models using Moderation