Introduction As discussed in the previous post, I’ve recently constructed and delivered a short course on statistical computing with Scala. Much of the course is concerned with writing statistical algorithms in Scala, typically making use of the scientific and numerical computing library, Breeze. Breeze has all of the essential tools necessary for building statistical algorithms, … Continue reading scala-glm: Regression modelling in Scala
This is a practical tutorial on performing PCA on R. If you would like to understand how PCA works, please see my plain English explainer here. Reminder: Principal Component Analysis (PCA) is a method used to reduce the number of variables in a dataset. We are using R’s USArrests dataset, a dataset from 1973 showing, […]
This is a practical tutorial on performing PCA on R. If you would like to understand how PCA works, please see my plain English explainer here. Reminder: Principal Component Analysis (PCA) is a method used to reduce the number of variables in a dataset. We are using R’s USArrests dataset, a dataset from 1973 showing, […]
I always thought that there were some kind of schools in statistics, areas (not to say universities or laboratories) where people had common interest in term of statistical methodology. Like people with strong interest in extreme values, or in Lévy Processes. I wanted to check this point so I did extract information about articles puslished in about 35 journals in statistics, probability and econometrics. I got all the information in…
PDF available at here. Related post on KNN classification using SAS is here.In data mining and predictive modeling, it refers to a memory-based (or instance-based) algorithm for classification and regression problems. It is a widely used algorithm with...
SAS used to not support multithreading in PCA, then I figured out that its server version supports this functionality, see here. Today, I found this mutlithreading capability is finally available in PC SAS v9.22.The figure above indicates that all 4 th...
