In this post I continue with the unsupervised exploration of oil spectra, which we have seen in previous post ( PCA with "ChemoSpec" - 001).In the manual "ChemoSpec:An R Package for Chemometric Analysis of Spectroscopic Data", (page 23) there is a brie...
In my last post about "ChemoSpec package" (Hierarchical Cluster Analysis (ChemoSpec) - 02), we saw the two cluster groups (one for olive oil, other for sunflower oil), and also another sub-clusters for the sunflower oil.Continue reading the manual "Che...
This is a quick follow-up to my previous post about Color Palettes in RGB Space. Achim Zeileis had commented that, perhaps, it would be more informative to evaluate the color palettes in HCL (polar LUV) space, as that spectrum more accurately describes how humans perceive color. Perhaps more clear trends would emerge in HCL space,
Abstract Long-term daily precipitation records from the US Historical Climatology Network (USHCN) are processed and summarized using R. Below is R code which examines the data from Livermore, CA, the closest available USHCN station to my present home ...
Update (Dec 18, 2012): Please see this related post I wrote about differential isoform expression analysis with Cuffdiff 2.DESeq and edgeR are two methods and R packages for analyzing quantitative readouts (in the form of counts) from high-throughput e...
My amazing, awesome wife often comes up with the little puzzles for our amazing children, and this one seemed destined to be solved in R. So, using up to 5 coins (1p, 2p, 5p, 10p, 20p and 50p) first she asked our kids whether they could make every val...
When I learned about principal component analysis (PCA), I thought it would be really useful in big data analysis, but that's not true if you want to do prediction. I tried PCA in my first competition at kaggle, but it delivered bad results. This post illustrates how PCA can pollute good predictors.
When I started examining this problem,...
Why R:Actually, It is a common practice the integration of the statistical analysis of the resulted data and in silico predictions of the data generated in your manuscript and your daily research. Mass spectrometrist, biologist and bioinformaticians c...
In this tutorial I am going to share my R&D and trading experience using the well-known from statistics Autoregressive Moving Average Model (ARMA). There is a lot written about these models, however, I strongly recommend Introductory Time Series with R, which I find is a perfect combination between light theoretical background and practical implementations in
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
