Another semester has gone by. It was my third semester as a graduate student and was quite fun actually, although I was frequently haunted by the fear that I (for real in this time) might fail.
This time, I was enrolled in three lectures, audited (in some part of) one lecture and took one seminar class. To elaborate, I studied Real Analysis1, Non-parametric Function Estimation2 and Advanced data mining3, briefly attended to some classes of Seminar in Recent Development of Applied Statistics4 and attended to every seminars that were held by the department in this semester.
I knew that Real Analysis was one of the most important theory regarding statistics. Nonparametric methodology of estimating functions was also of my interest. For these reasons, I was so thrilled and enthusiastic at the start of the semester that I wanted to organize the contents to my blog right after I finished reviewing what I learned in the lecture.
As the semester passes by, my grand plan has clearly failed (from April 21) due to overwhelming loads I faced. The plan-B was to review them after the end of the semester. However, my current interest lies on the nonparametric shape-constrained estimation. To understand what is happening in this field, I would like to review Empirical processes in M-estimation (van de Geer, 2000) for the following series of posts, which I learned some in the second semester of 2020.
So yeah, this is an article-long excuse to myself, pretending to be a retrospection for the last semester.