I’ve been looking at the following paper, by researchers at Harvard’s school of public health, which was recently published in Science: Kissler, Tedijanto, Goldstein, Grad, and Lipsitch (2020) Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period (also available here, with supplemental materials here). This is one of ...

Binary Logistic Regression is used to explain the relationship between the categorical dependent variable and one or more independent variables. When the dependent variable is dichotomous, we use binary logistic regression. However, by default, a binary logistic regression is almost always called logistics regression. Overview – Binary Logistic Regression The logistic ...

In this tutorial on purrr package in R, you will learn how to use functions from the purrr package in R to improve the quality of your code and understand the advantages of purrr functions compared to equivalent base R functions.

Data science is one of the most wide-ranging disciplines of the 21st century. Data scientists use a wide variety of methods and tools to generate more knowledge from data and its analysis. Especially in times like today, data and the insights we can draw from them are becoming increasingly important. ...

Data Scientists Face an Existential Crisis The term data scientist has always been a bit controversial. William Cleveland coined the term in 2001 to advocate the practical use of statistics in other technical fields and believed that use warranted a n...

Survival Analysis Survival analysis deals with estimating probability of continuation of a particular status-quo at given point in time. Naturally, it also estimates the probability of discontinuation of the status quo i.e. occurance of an event or a hazard. It finds application in several fields. For e.g. in ...

Lately I’ve been publishing screencasts demonstrating how to use the tidymodels framework, from first steps in modeling to how to evaluate complex models. Today’s screencast isn’t about predictive modeling, but about unsupervised machine learning using with this week’s #TidyTuesday dataset on cocktail recipes. ???? Here is the ...

Introduction The idea behind this post was to play and discover some of the info contained in the COVID19 R package which collects data across several governmental sources.This package is being developed by the Guidotti and Ardia from COVID19 Data Hub. Later, I will add to the analysis the ...

As you are likely aware by now, the dplyr 1.0.0 release is right around the corner. I am very excited about this huge milestone for dplyr. In this post, we’ll go over my favorite new features coming in the 1.0.0 release.

# Install development version of dplyr
remotes::install_github(
  "tidyverse/dplyr", 
  ref = "23c166fa7cc247f0ee1a4ee5ac31cd19dc63868d"
)

Note: in the above call to install_github(), I ...

COVID-19 disease spread hit the World really globally and also the field of mathematicians/ statisticians/ machine learning researchers and related. These experts want to help to understand for example future trends (forecast) of the coronavirus spread...

This post will look at how to fit an XGBoost model using the tidymodels framework rather than using the XGBoost package directly. Tidymodels is a collection of packages that aims to standardise model creation by providing commands that can be applied across different R packages. For example, once the code ...