Paper’s review: Zhu & Fang, 1996. Asymptotics for kernel estimate of sliced inverse regression.

It is already known, that for $latex { Y\in {\mathbb R} }&fg=000000$ and $latex { X \in {\mathbb R}^{p} }&fg=000000$, the regression problem $latex \displaystyle Y = f(\mathbf{X}) + \varepsilon, &fg=000000$ when $latex { p }&fg=000000$ is larger than the data available, it is well-known that the curse of dimensionality problem arises. Richard E. Bellman […]

The return

Photo from Paolo Dala Hola, Hello, Bonjour! It’s good to return to the blogging stream. I’ve been somewhat disconnected these months. A little distracted, with a drought of ideas and a little unmotivated,… I think that it happens, to all of us. At least didn’t happen to me like it did to poor Chuck….