Clojure is such an interesting programming language that it can not only enhance our skill set but also change the way how we should write the program. After learning Clojure,...continue reading.
When it comes to writing wrappers around data steps and procedures in SAS, SAS macros might still be the primary choice for most SASors. In the example below, I am...continue reading.
As a journal editor, I often receive studies in which the investigators fail to describe, analyse, or even acknowledge missing data. This is frustrating, as it is often of the...continue reading.
In the previous post (https://statcompute.wordpress.com/2018/08/26/adjacent-categories-and-continuation-ratio-logit-models-for-ordinal-outcomes), we’ve shown alternative models for ordinal outcomes in addition to commonly used Cumulative Logit models under the proportional odds assumption, which are also known as...continue reading.
Hi, Two years ago I blogged about couplings of conditional particle filters for smoothing. The paper with Fredrik Lindsten and Thomas Schön has just been accepted for publication at JASA, and the arXiv...continue reading.
In the previous post (https://statcompute.wordpress.com/2018/01/28/modeling-lgd-with-proportional-odds-model), I’ve shown how to estimate a standard Cumulative Logit model with the ordinal::clm function and its use case in credit risk models. To better a...continue reading.
Hi, Just to play a bit with the gganimate package, and to celebrate National Coupling Day, the above plot shows different couplings of two univariate Normal distributions, Normal(0,1) and Normal(2,1)....continue reading.
Today is the first day of the new academic year at the University of Utah. This semester I am teaching MATH 3070: Applied Statistics I, the fourth time I’ve taught...continue reading.
The analysis of high frequency stock transactions has played an important role in the algorithmic trading and the result can be used to monitor stock movements and to develop trading...continue reading.
Linear programming is a technique to solve optimization problems whose constraints and outcome are represented by linear relationships.Simply put, linear programming allows to solve problems of the following kind:Maximize/minimize $\hat...continue reading.
This is a short post following the previous one (PCA revisited).In this post I’m going to apply PCA to a toy problem: the classification of faces. Again I’ll be working...continue reading.
Principal component analysis (PCA) is a dimensionality reduction technique which might come handy when building a predictive model or in the exploratory phase of your data analysis. It is often...continue reading.
I can’t count how many times I have looked up the formal (measure theoretic) definitions of conditional probability distribution or conditional expectation (even though it’s not that hard :weary:) Another...continue reading.
Thanks to Rasmus Bååth for some comments and encouragement. When I decided to start my own business doing training in … Morecontinue reading.
Most SAS procedures require the RUN; statement to signal their termination. However, there are some notable exceptions to this. I have written about PROC SQL many times on my blog,...continue reading.
This post is in a series that take one image from my book Data Visualization: charts, maps and interactive graphics, … Morecontinue reading.
The co-integration is an important statistical concept behind the statistical arbitrage strategy named “Pairs Trading”. While projecting a stock price with time series models is by all means difficult, it...continue reading.
For More posts on Bayesian models, Bayesian Nonparametrics, and causal inference follow me on twitter @stablemarkets. My advisor and his collaborator are teaching a short course on Bayesian Nonparametric Methods...continue reading.
I am pleased to welcome Arnab Chakraborty back to my talk show, “The Central Equilibrium“, to talk about the Monty Hall Problem and Bayes’ theorem. In this episode, he shows...continue reading.
Hi, This post is about different ways of using Markov chain Monte Carlo (MCMC) algorithms for numerical integration or sampling. It can be a hard job to design an MCMC...continue reading.
Artificial intelligence / Deep neural networks / Keras / R / R News / Spark
April 22, 2024
GIS / R / R News / Shiny / Visualization
Interactive visualization of geospatial data with R Shiny
April 17, 2021
