As data analysts, we’re frequently presented with comma-separated value files and tasked with reporting insights. While it’s tempting to import that data directly into R or Python in order to...continue reading.
Recently, Matt Motyl et al. (2017) posted a pre-print paper in which they contrasted the evidential value of several journals in two time periods (2003-2004 vs. 2013-2014). The paper sparked...continue reading.
I’m a fan of Chris Albon’s recent project #machinelearningflashcards on Twitter where generalized topics and methodologies are drawn out with key takeaways. It’s a great approach to sharing concepts about...continue reading.
I’m a fan of Chris Albon’s recent project #machinelearningflashcards on Twitter where generalized topics and methodologies are drawn out with key takeaways. It’s a great approach to sharing concepts about...continue reading.
Rent Prices are Soaring in Most of Colorado Call it gentrification, supply-and-demand, call it whatever you’d like… the fact is, rent prices have gone up in Colorado in the last...continue reading.
In the previous post (https://statcompute.wordpress.com/2016/11/27/more-about-flexible-frequency-models), I’ve shown how to estimate the double Poisson (DP) regression in R with the gamlss package. The hurdle of estimating DP regression is the calculation...continue reading.
As shown by Fu and Wu in their presentation (https://www.casact.org/education/rpm/2010/handouts/CL1-Fu.pdf), the quantile regression is an appealing approach to model severity measures with high volatilities due to its statistical characteristics, including...continue reading.
What Type of Data Visualization Do You Choose (if any)? Determining whether or not you need a visualization is step one. While it seems silly, this is probably something everyone...continue reading.
Conway-Maxwell-Poisson (CMP) regression is a flexible way to model frequency outcomes with both under-dispersion and over-dispersion. In SAS, CMP regression can be estimated with COUNTREG procedure directly or with NLMIXED...continue reading.
A Quick Overview of the ggplot2 Package in R While it will be important to focus on theory, I want to explain the ggplot2 package because I will be using...continue reading.
Introduction to Data Visualization – Theory, R & ggplot2 The topic of data visualization is very popular in the data science community. The market size for visualization products is valued...continue reading.
The Generalized Poisson (GP) regression is a very flexible statistical model for count outcomes in that it can accommodate both over-dispersion and under-dispersion, which makes it a very practical modeling...continue reading.
The R qgraph Package: Using R to Visualize Complex Relationships Among Variables in a Large Dataset, Part One A Tutorial by D. M. Wiig, Professor of Political Science, Grand View...continue reading.
We have 2 legends, Biggie Smalls and Nas. At the 1:00 mark, Nasty Nas receives a Nasty Rubdown. Pretty sure this was the inspiration for Boosie’s Wipe Me Down. I made...continue reading.
Here I am after a short break, writing again about R!In december I worked on a project that required me to work on spatial data. This led me to learn...continue reading.
We the moody Gucci, Louis and Pucci men Escada, Prada The chopper it got the Uzi lens Bird’s-eye view The birds I knew, flip birds Bird gangs, it was birds...continue reading.
The R package smbinning (https://cran.r-project.org/web/packages/smbinning/index.html) provides a very user-friendly interface for the WoE (Weight of Evidence) binning algorithm employed in the scorecard development. However, there are several improvement opportunities in...continue reading.
by Angelika Stefan & Felix Schönbrodt This is the second part of “Two meanings of priors”. The first part explained a first meaning – “priors as subjective probabilities of models”....continue reading.
A Tutorial by D. M. Wiig The R programming language has a multitude of packages that can be used to display various types of graph. For a new user looking...continue reading.
There is a plethora of classification algorithms available to people who have a bit of coding experience and a set of data. A common machine learning method is the random...continue reading.
