GARCH (generalized autoregressive conditional heteroscedasticity) models are widely used in market risk industry to estimate and forecast the volatility of returns. GARCH, including many variants like A-GARCH, GJR-GARCH and E-GARCH, is especially suit…
Tag: R
Automate univariate volatility modeling by macros
GARCH (generalized autoregressive conditional heteroscedasticity) models are widely used in market risk industry to estimate and forecast the volatility of returns. GARCH, including many variants like A-GARCH, GJR-GARCH and E-GARCH, is especially suit…
R for SAS and SPSS Users, A Review
If you’ve followed me for any length of time, you’ll know that I’m bullish on good data analysis. I am not a programmer by training but, through a variety of projects, I’ve found a solid understanding of data manipulation has … Continue reading →
A macro calls random forest in SAS
SASHELP.CARS, with 428 observations and 15 variables, is a free dataset in SAS for me to exercise any classification methods. I always have the fantasy to predict which country a random car is manufactured by, such as US, Japan or Europe. After tryi…
Support vector machine for classification in SAS by R
I just recently discovered endless fun to synchronize SAS and R to do something meaningful. Yep, I am a SAS programmer: during the day time, I use SAS for money; at the evening, I use R for fun. It is always exciting to hook up them together. How abo…
A macro calls R in SAS for paneled 3d plotting
SAS and R could complement each other. SAS is a versatile ETL (extraction, transformation and loading) machine and its statistical procedures based on generalized linear model are impeccable. R would bring cutting-edge data mining and data visualizatio…
Progress reading SAS sas7bdat files (natively) in R
This post describes some preliminary results from a compatibility study of the SAS sas7bdat file format. The most current results stored in a github repository here: sas7bdat The ultimate goal is a native solution to the incompatibility between open-source statistical software (e.g. R) and sas7bdat database files. Demonstration There has been significant progress in interpreting […]
Regularized Discriminant Analysis
Demo SAS implementation of Regularized (Linear) Discriminate Analysis of J. Friedman (1989)[1]. Simpler introduction can be found at [2]. Regularized QDA follows similarly.
To save coding, I called R within SAS to finish the computation. For details…