Data Science Live Book (open source) ~ new big release! 200-pages
New big release (200-pages) in the Data Science Live Book -open source- Download available in PDF, eBook and Kindle versions!continue reading.
New big release (200-pages) in the Data Science Live Book -open source- Download available in PDF, eBook and Kindle versions!continue reading.
Introduction McDonald’s is a nostalgic component of America ?? and a pioneer of fast food operations and real estate ventures, as depicted in the 2016 film, The Founder, about Ray...continue reading.
Introduction McDonald’s is a nostalgic component of America ?? and a pioneer of fast food operations and real estate ventures, as depicted in the 2016 film, The Founder, about Ray...continue reading.
For those who aren’t familiar with the colourpicker package, it provides a colour picker for R that can be used in Shiny, as well as other related tools. Today it’s...continue reading.
I have a character string snipped from a lyric by Daniel Son the Necklace Don. Let’s get all Weird Al Yankovic with it. I’ll revise some words with the datzen::yankovise()...continue reading.
This is a somewhat belated introduction of a package that we published on CRAN at the beginning of the year already, but I hadn’t found the time to blog about this earlier....continue reading.
Ahh, leaves falling, parents crying, collegicians biking uphill with a bag of in-n-out in between their teeth. Must be the new academic school year! I figured it’s a good time...continue reading.
This week I’ve been looking at two models in R that are attempting to predict whether Giancarlo Stanton would break Roger Maris’ mark of 61 home runs in a season....continue reading.
While the monotonic binning algorithm has been widely used in scorecard and PD model (Probability of Default) developments, the similar idea can be generalized to LGD (Loss Given Default) models....continue reading.
Sometimes, events move faster than we predict them. This is one of the things that makes statistics as much of an art as a science. Last night, Giancarlo Stanton hit...continue reading.
Two posts today with similar themes. Time is running out. First, time is running out for Giancarlo Stanton. His bat has been very silent this week so far. The Marlins...continue reading.
Microsoft Cognitive Services Vision API in R A little while ago I did a brief tutorial of the Google Vision API using RoogleVision created by Mark Edmonson. I couldn’t find...continue reading.
The regular Major League Baseball season is coming to an end. Next week, we move into the playoffs and eventually the World Series. However, we have a nice statistical modeling...continue reading.
In the post (https://statcompute.wordpress.com/2017/06/15/finer-monotonic-binning-based-on-isotonic-regression), it is shown how to do a finer monotonic binning with isotonic regression in R. Below is a SAS macro implementing the monotonic binning with the...continue reading.
Exploratory Data Analysis of Tropical Storms in R The disastrous impact of recent hurricanes, Harvey and Irma, generated a large influx of data within the online community. I was curious...continue reading.
As mentioned in the previous post (https://statcompute.wordpress.com/2017/06/29/model-operational-loss-directly-with-tweedie-glm/), we often need to model non-negative numeric outcomes with zeros in the operational loss model development. Tweedie GLM provides a convenient interface to...continue reading.
I am excited to announce the release of mathpy 0.3.0! This release adds a ton of Excel UDFs including many new statistical and number-theoretic functions, several random number generators and…...continue reading.
In a previous post, I derived and coded a Gibbs sampler in R for estimating a simple linear regression. In this post, I will do the same for multivariate linear...continue reading.
LASSO has been a popular algorithm for the variable selection and extremely effective with high-dimension data. However, it often tends to “over-regularize” a model that might be overly compact and...continue reading.
Abstract Control calculation ping-pong is the process of iteratively improving a statistical analysis by comparing results from two independent analysis approaches until agreement. We use the daff package to simplify...continue reading.