# 2223 search results for "regression"

## Introduction to Feature selection for bioinformaticians using R, correlation matrix filters, PCA & backward selection

October 17, 2013
By

Bioinformatics is becoming more and more a Data Mining field. Every passing day, Genomics and Proteomics yield bucketloads of multivariate data (genes, proteins, DNA, identified peptides, structures), and every one of these biological data units are described by a number of features: length, physicochemical properties, scores, etc. Careful consideration of which features to select when trying...

## A Bayesian Model for a Function Increasing by Chi-Squared Jumps (in Stan)

October 16, 2013
By

(This article was first published on David Chudzicki's Blog, and kindly contributed to R-bloggers) This post will describe a way I came up with of fitting a function that’s constrained to be increasing, using Stan. If you want practical help, standard statistical approaches, or expert research, this isn’t the place for you (look up “isotonic regression” or “Bayesian isotonic...

## That’s Smooth

October 10, 2013
By

I had someone ask me the other day how to take a scatterplot and draw something other than a straight line through the graph using Excel.  Yes, it can be done in Excel and it’s really quite simple, but there are some limitations when using the stock Excel dialog screens. So it is probably in

## Please, never use my codes without checking twice (at least)!

October 9, 2013
By

I wanted to get back on some interesting experience, following a discussion I had with Carlos after my class, this morning. Let me simplify the problem, and change also the dataset. Consider the following dataset > db = read.table("http://freakonometrics.free.fr/db2.txt",header=TRUE,sep=";") Let me change also one little thing (in the course, we use the age of people as explanatory variables, so...

## Fast Bayesian Inference with INLA

October 9, 2013
By

I am currently a research fellow and 4th year PhD candidate within the INLA group.  If you deal with Bayesian models and have never heard about INLA, I sincerely think you should spend a small portion of your time to at least know what it is. If you have heard about it before, you know how nice

## Some heuristics about spline smoothing

October 8, 2013
By
$\mathbb{E}(Y\vert X=x)=h(x)$

Let us continue our discussion on smoothing techniques in regression. Assume that . where is some unkown function, but assumed to be sufficently smooth. For instance, assume that  is continuous, that exists, and is continuous, that  exists and is also continuous, etc. If  is smooth enough, Taylor’s expansion can be used. Hence, for which can also be writen as for...

## Too crude to be true?

October 8, 2013
By

The key to programming is being lazy; it has actually been called a virtue by some. When I discovered the update() function it blew me away. Within short I had created a monster based upon this tiny function, allowing quick and easy output of regression tables that contain crude and adjusted estimates. In this post I’ll show...

## Sensitivity analysis for neural networks

October 7, 2013
By

I’ve made quite a few blog posts about neural networks and some of the diagnostic tools that can be used to ‘demystify’ the information contained in these models. Frankly, I’m kind of sick of writing about neural networks but I wanted to share one last tool I’ve implemented in R. I’m a strong believer that

## Questions on my online forecasting course

October 3, 2013
By

I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers. Do I need to use the Revolution Enterprise version of R, or can I use open-source R? Open source R is fine. Revolution Analytics is organizing the course, but there is no requirement to use their software. I will be using...

## R and Data Week 2013

October 3, 2013
By

by Joseph Rickert Data Week 2013 is being held this week in sunny San Francisco at the Fort Mason conference center overlooking the Bay. Holding a Bay Area R User Group Meeting (BARUG) at Data Week helped to raise the R consciousness among the hip conference crowd attracted by the intoxicating mix of blue skies, big data hype, startups...