30 Dec

Hi! It’s been a while. How’s it going?

Around here, things are moving. They’re moving quickly. I’ve heard my professors say that a PhD is a weird time in life, because nothing really happens or changes for years in the middle of it, and then at the end EVERYTHING HAPPENS Read More

24 Dec

Part of my educational duties this past semester was as a teaching assistant for an undergraduate introductory biostatistics course. We went over the usual topics—calculating probabilities from tables, test statistics, hypothesis testing, linear and logistic regression—and I felt that the curriculum made a great effort to contextualize the material by Read More

19 Dec

I've been doing some classification with logistic regression in brain imaging recently. I have been using the ROCR package, which is helpful at estimating performance measures and plotting these measures over a range of cutoffs.

The prediction and performance functions are the workhorses of most of the analyses in ROCR Read More

18 Dec

In my last post I described some of my commonly done ggplot2 graphs. It seems as though some people are interested in these, so I was going to follow this up with other plots I make frequently.

## Scatterplot colored by continuous variable

The setup of the data for the scatterplots Read More

10 Dec

## As a user

Imagine that you are starting to learn how to use a specific R package, lets call it foo. You will look at the vignette (if there is one), use help(package = foo), or look at the reference manual (for example, devtools’ ref man). Eventually, you Read More

20 Nov

This is a guest post by Prasad Patil that answers the question: how to put a shape in the margin of an R plot?

The help page for R‘s par() function is a somewhat impenetrable list
of abbreviations that allow you to manipulate anything and everything

04 Nov

This was originally written on Nov 3, 2013.

Converted from .tex using latex2wp.

Usually, we say a random variable ${X}$ follows a Normal(0,1) distribution, if its cumulative distribution can be expressed as:

$\displaystyle P\{X\leq t\}=\int_{-\infty}^{t}\frac{1}{\sqrt{2\pi}}e^{-\frac{x^{2}}{2}}dx.$

Now we formalize this in a more measure-theoretic way, in correspondence to what we learned in the course, particularly, Read More

04 Nov

This was originally written on Nov 25, 2013.

Converted from .tex using latex2wp.

In this note, we explained why the conditional expectation of a random variable ${Y}$ given a ${\sigma}$-field ${\mathscr{G}}$ can be seen as “smoothed version of ${Y}$ over ${\mathscr{G}}$” (in Example 2), and we briefly related the definition of conditional expectation Read More