In my final post on setting up yearly goals I will write about how to track progress and finally add some data visuals. Building your own progress dashboards adds a nice meta level of data science to the journey and gives you more control over how to track your goals. ...

Are you interested in guest posting? Publish at DataScience+ via your RStudio editor.CategoryAdvanced ModelingTagsData VisualisationHodgkin & Huxley modelR ProgrammingShiny appIntroduction In this second part we will present a numerical method for solving the PDE system, which describes the propagation of action potential. We will make use of the R-Packages deSolve ...

If you’re a graduate of economics, psychology, sociology, medicine, biostatistics, ecology, or related fields, you probably have received some training in statistics, but much less likely in machine learning. This is a problem because machine-learning algorithms are much better capable to solve many real-world applications compared with the procedures ...

tldr: You can now use polished to secure Rmarkdown documents that use the shiny runtime. This includes flexdashboards! For example, if you have a flexdashboard that uses shiny. e.g. Your Rmd Shiny App With a single function call, you can add a...

I have recently updated my detailed reviews of Graphical User Interfaces (GUIs) for R, so it’s time for another comparison post. It’s not too difficult to rank them based on the number of features they offer, so let’s start there. I’m basing the counts on the ...

Today I’m excited to share a blog post on how to use R Markdown. R Markdown is a dynamic file format that allows you to make documents containing normal text alongside chunks of embedded R code. In fact, all of my blog posts are written using R M...

The post How to calculate Power Regression in R (Step-by-Step Guide) appeared first on finnstats. If you want to read the original article, click here How to calculate Power Regression in R (Step-by-Step Guide). Power Regression in R, Power regression is a non-linear regression technique that looks like this: y = ...

Cover photo by Mehdi Sepehri on Unsplash Go to R-bloggers for R news and tutorials contributed by hundreds of R bloggers. Introduction This article is part of the series (Swarm) Portfolio Optimization. I assume you have read the Nonparametric VaR artic...

Data visualization is important. It’s so important that how you present your data can affect the success of an app or project. For applications that make heavy use of data, data visualization best practices can significantly increase the level of adoption. On the other hand, if the data is ...

I did a tweet earlier which was slightly less nonsense than usual. Shocker, I know.

The package simstudy has some functions that facilitate generating survival data using an underlying Weibull distribution. Originally, I added this to the package because I thought it would be interesting to try to do, and I figured it would be use...

Recent Advances in Approximate Bayesian Inference In approximate Bayesian computation, likelihood function is intractable and needs to be itself estimated using forward simulations of the statistical model (Beaumont et al., 2002; Marin et al., 201...

Andrea Luciani is a Technical Advisor for the Directorate General for Economics, Statistics and Research at the Bank of Italy, and co-author of the bimets package. Introduction In this post, I show how to analyze the forecast error for a Structural Equation Model (SEM) by means of a stochastic simulation, ...

Snowflake is a well known cloud-based database. It’s used for Data Warehouses and other big data applications. In this article and the following ones I want to show how to setup and access a snowflake database from various clients such as R, Tableau and PowerBI. So let’s start ...

You can see the recorded presentation below of the RBelgium session we held last week (on Thursday 2022-02-03). Christophe Regouby (co-author of the tabnet R package) talked about the design of the the recent torch R package which interfaces with the ...

Recent Advancements in Applied Instrumental Variable Methods Instrumental variables (IV) is one of most important and widespread research designs in economics and statistics, as it can identify causal effects in the presence of unobserved confound...