I am a statistical consultant and R enthusiast.

I believe in the use of data science for social good and have worked with several non-profit organizations.

How to implement PCA from scratch in R

What is PCA ? Principal component analysis (PCA) is an approach based on the singular value decomposition of the data. The goal of PCA is reduce the dimension of the data you are using by projecting this data into the sub-space The french school of ‘Analyse des donnĂ©es’ It focuses on geometrical summary(cars)## speed dist ## Min. : 4.0 Min. : 2.00 ## 1st Qu.:12.0 1st Qu.: 26.00 ## Median :15. [Read More]

Test syntax highlight

Hello world

A small test

summary(cars)
##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Regression test

fit = lm(dist ~ speed, data = cars)
b = coef(summary(fit))
plot(fit)

Linked post

I’m a linked post in the menu. You can add other posts by adding the following line to the frontmatter: menu = "main" Lorem ipsum dolor sit amet, consectetur adipiscing elit. In mauris nulla, vestibulum vel auctor sed, posuere eu lorem. Aliquam consequat augue ut accumsan mollis. Suspendisse malesuada sodales tincidunt. Vivamus sed erat ac augue bibendum porta sed id ipsum. Ut mollis mauris eget ligula sagittis cursus. Aliquam id pharetra tellus. [Read More]