Changepoint Detection : Theoretical Background

Introduction Changepoints are abrupt variations in the generative parameters of sequential data. Changepoint detection is the process of identifying such abrupt variations and it has been useful in a wide range of applications such as EEG analysis, DNA segmentation, econometrics etc. Bayesian ways of ¬†change point detection focus on segmentation and techniques to generate samples…

My Experience with GSOC and R

It all began when I started searching for a Google Summer of Code project last year (November, 2015) . While I was searching through the web found this page that suggested of a project idea. I didn’t have a complete understanding about the problem but I contacted the mentors and familiarized myself with R and…

postCP change point detection with GSOC

  Introduction to postCP The project aimed at improving the postCP package and making it available on CRAN again. The snag that prevented the package from being updated is the recent requirement that in the R code, .C() calls require DUP=TRUE arguments, and .Call() is suggested instead of .C(). The implementation of postCP package required…

Gauge Meters; A daunting task

Since I’m on vacation, I thought of planning my project using the free time. As the next step, I thought of developing the front end of the application. The user should be able to view the real time temperature and the power consumption. To present this information, I thought of using simple gauge meters. Although…

Air Conditioning? Big Deal?

Last week we were assigned projects for our 4th semester and I was selected for the energy sector. As a part of it, when I was exploring the subject, my attention was driven towards Centralized Air Conditioning Systems. My biggest concern was, does that amount to a significant proportion of the total energy consumption. Based…