In praise of sparsity and convexity

When asked to reflect on an anniversary of their field, scientists in most fields would sing the praises of their subject. As a statistician, I will do the same. However, here the praise is justified! Statistics is a thriving discipline, more and more an essential part of science, business and societal activities. Class enrollments are up—it seems that everyone wants to be a statistician—and there are jobs everywhere. The field of machine learning, discussed in this volume by my friend Larry Wasserman, has exploded and brought along with it the computational side of statistical research. Hal Varian, Chief Economist at Google, said “I keep saying that the sexy job in the next 10 years will be statisticians. And I’m not kidding.” Nate Silver, creator of the New York Times political forecasting blog “538” was constantly in the news and on talk shows in the runup to the 2012 US election. Using careful statistical modelling, he forecasted the election with near 100% accuracy (in contrast to many others). Although his training is in economics, he (proudly?) calls himself a statistician. When meeting people at a party, the label “Statistician” used to kill one’s chances of making a new friend. But no longer! In the midst of all this excitement about the growing importance of statistics, there are fascinating developments within the field itself. Here I will discuss one that has been the focus my research and that of many other statisticians.