# 268 search results for "pca"

## Genetic data, large matrices and glmnet()

February 25, 2014
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Recently talking to a colleague, had contact with a problem that I had never worked with before: modeling with genetic The post Genetic data, large matrices and glmnet() appeared first on Flavio Barros .

## Interactive exploration of a prior’s impact

February 21, 2014
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The probably most frequent criticism of Bayesian statistics sounds something like “It’s all subjective – with the ‘right’ prior, you can get any result you want.”. In order to approach this criticism it has been suggested to do a sensitivity analysis (or robustness analysis), that demonstrates how the choice of priors affects the conclusions drawn

## Regression with multiple predictors

February 18, 2014
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(This article was first published on Digithead's Lab Notebook, and kindly contributed to R-bloggers) Now that I'm ridiculously behind in the Stanford Online Statistical Learning class, I thought it would be fun to try to reproduce the figure on page 36 of the slides from chapter 3 or page 81 of the book. The result is a curvaceous surface...

## ggplot2: Cheatsheet for Visualizing Distributions

February 18, 2014
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In the third and last of the ggplot series, this post will go over interesting ways to visualize the distribution of your data.

## Tutorials- Statistical and Multivariate Analysis for Metabolomics

February 17, 2014
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I recently had the pleasure in participating in the 2014 WCMC Statistics for Metabolomics Short Course. The course was hosted by the NIH West Coast Metabolomics Center and focused on statistical and multivariate strategies for metabolomic data analysis. A variety of topics were covered using 8 hands on tutorials which focused on: data quality overview

## Unprincipled Component Analysis

February 10, 2014
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As a data scientist I have seen variations of principal component analysis and factor analysis so often blindly misapplied and abused that I have come to think of the technique as unprincipled component analysis. PCA is a good technique often used to reduce sensitivity to overfitting. But this stated design intent leads many to (falsely) Related posts:

## ShareLaTeX now supports knitr

January 31, 2014
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ShareLaTeX (click here to register a free account) is a wonderful and reliable on-line editor for writing and compiling LaTeX documents “in the cloud” as well as working together in real-time (imagine Google Docs supporting LaTeX => you get ShareLaTeX).…Read more ›

## Using Last.fm to data mine my music listening history

I've (passively) been keeping meticulous records of almost every song I've listened to since January of 2008. Since I opened my last.fm account 6 years ago, they've accumulated a massive detailed dataset of the 107,222 songs I've listened to since then. The best thing is that they're willing to share this data with me! I »more

## Computing and visualizing LDA in R

January 15, 2014
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$Computing and visualizing LDA in R$

As I have described before, Linear Discriminant Analysis (LDA) can be seen from two different angles. The first classify a given sample of predictors to the class with highest posterior probability . It minimizes the total probability of misclassification. To compute it uses Bayes’ rule and assume that follows a Gaussian distribution with class-specific mean