I have tested several R optimization functions before: nlm, optim(Nelder-Mead), optim(BFGS), optim(SANN), nlminb, optim (L-BFGS-B) for a eight-parameter Vasicek interest rate model, overall I find that for my setting, nlminb is the best and all R func...
Dr. Patrick Burns is the founder of Burns Statistics, providing consulting and bespoke software specializing in quantitative finance, programming in the S language, and optimization via genetic algorithms and simulated annealing. Patrick has written m...
Happy last month of 2011. I will fly to Sydney to present a paper at the 24th Australasian Finance & Banking Conference on next Thursday, so we may not have a review next week. However, feel free to contact me @a_biao for sharing any useful post. This week's review is highly concentrated on
Examining the determinants of credit default swap (CDS) spreads is a hot topic, CDS spread has displayed siginificant regime switching behaviour since the break of credit crisis, which can be seen from the old graph in the post Credit Default Spread a...
Got to know a very cool tool to use R in Excel named RExcel, basically it provides an integration solution such that users can get data, run command in Excel the same way as in R, which is presumably good and convenient to present results to your coll...
Some of you may hear that the new release of R 2.13.0 is out, with some Windows-specific changes to R 2.13.0:
file.exists() and unlink() have more support for files > 2GB;
A few more file operations will now work with >2GB files.
which could help us to relieve the worry of handling large datasets in R.
Could any R expert here help me to vectorize my for loop? Thanks in advance for your favor. The reason I am in trouble is the variable inside my "for" function are updated after each loop, which makes me feel difficult to use lapply, sapply or whatever.
Simplifed codes are listed below:
The Google Prediction API is a black-box system for building predictive models, it provides pattern-matching and machine learning capabilities. So Google algorithms automatically creates a model from the training models given a set of training data and makes prediction under this model given a set of explanatory variables, read http://code.google.com/apis/predict/docs/getting-started.html for an overview.
I am eager...
Life is short, use Python
I started to play with Python two weeks ago due to the limitation of R in terms of handling large data, then a friend of mine suggested me to try Python since I had to do data massage frequently, "Python is the best choice, trust me", he...
Handling large dataset in R, especially CSV data, was briefly discussed before at Excellent free CSV splitter and Handling Large CSV Files in R. My file at that time was around 2GB with 30 million number of rows and 8 columns. Recently I started to collect and analyze US corporate bonds tick data from year...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
