# 167 search results for "PCA"

## Eigen-analysis of Linear Model Behavior in R

May 7, 2013
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This post is actually about replicating the figures in Otto and Day: A Biologist’s Guide to Mathematical Modeling in Ecology and Evolution. The figures I’m interested in for this post are Figures 9.1 and 9.2 in the chapter ‘General Solutions … Continue reading

## Using the SVD to find the needle in the haystack

April 19, 2013
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(This article was first published on G-Forge » R, and kindly contributed to R-bloggers) Sitting with a data set with too many variables? The SVD can be a valuable tool when you’re trying to sift through a large group of continuos variables. The image is CC by Jonas in China. It can feel like a daunting task when you...

## Reconstructing Principal Component Analysis Matrix

April 5, 2013
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PCA is widely used method for finding patterns in high-dimensional data. Whether you use it to compress large matrix or to remove one of the principal components in biological datasets, you’ll end up with the task of performing series of … Continue reading

## Veterinary Epidemiologic Research: GLM (part 4) – Exact and Conditional Logistic Regressions

March 22, 2013
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Next topic on logistic regression: the exact and the conditional logistic regressions. Exact logistic regression When the dataset is very small or severely unbalanced, maximum likelihood estimates of coefficients may be biased. An alternative is to use exact logistic regression, available in R with the elrm package. Its syntax is based on an events/trials formulation.

## Violin plots and regional income distribution

March 20, 2013
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While preparing my slides for statistical graphics, a plot really caught my eye when I was playing around with the data.

I started off by plotting the time seriesof GNI per capita by country, and as expected it got quite messy and...

## Evaluation of Orthogonal Signal Correction for PLS modeling (OSC-PLS and OPLS)

March 15, 2013
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Partial least squares projection to latent structures or PLS is one of my favorite modeling algorithms. PLS is an optimal algorithm for predictive modeling using wide data or data with  rows << variables. While there is s a wealth of literature regarding the application of PLS to various tasks, I find it especially useful for biological

## reading raster data using library(parallel)

March 3, 2013
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Recently, I have been doing some analysis for a project I am involved in. In particular, I was interested what role pacific sea surface temperatures play with regard to rainfall in East Africa. I spare you the details as I … Continue reading

## PCA to PLS modeling analysis strategy for WIDE DATA

March 2, 2013
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Working with wide data is already hard enough, add to this row outliers and things can get murky fast. Here is an example of an anlysis of a wide data set, 24 rows  x 84 columns. Using imDEV, written in R, to calculate and visualize a principal components analysis (PCA) on this data set. We find that

## Shading and Points with xtsExtra plot.xts

February 28, 2013
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For some reason, I feel like have much better control with plot.xts function from the xtsExtra package described here over some of the other more refined R graphical packages. Maybe, it is just my simple mind, but recently I wanted to shade holding per...