[Ml-stat-talks] Wilks Statistics Seminar on Friday: Norden Huang (National Central University)

Lucy Xia lxia at princeton.edu
Wed Oct 23 11:03:00 EDT 2013


Hi All,

This friday's wilks seminar will be given by prof. Norden Huang from
Taiwan. He is well known for his contribution in the field of nonstationary
and nonlinear data analysis. Detailed info. for the talk please see below,
will be a very interesting talk!

Lucy

=== Wilks Statistics Seminar ===

DATE:   Friday, October 25

TIME:   12:30pm

LOCATION:   Sherrerd Hall 101

*SPEAKER*:  Norden Huang, National Central University

*TITLE*:   A Plea for Adaptive Data Analysis

*ABSTRACT*: Data analysis is indispensable to every scientific endeavors.
The existing data analysis methods are all developed by mathematicians
based on their rigorous rules. In pursue of the rigor, we are forced to
make idealized assumptions and live in a pseudo-real linear and stationary
world, in which data analysis is relegated to data processing. But the
world we live in is neither stationary nor linear. As scientific research
getting increasingly sophistic, the inadequacy of mere processing data
becomes glaringly obvious. To get the truth containing in the data, we have
to break away from these limitations; we should let data speak for
themselves so that the results could reveal the full range of consequences
of nonlinearity and nonstationarity. To do so, we need new paradigm of data
analysis methodology without a priori basis to fully accommodating the
variations of the underlying driving mechanisms. The solution lies in
adaptive data analysis approach. One example is the Empirical Mode
Decomposition method and the associated extensions of time-frequency
representation. We will show that, with the adaptive method, we can also
determine trend objectively. In fact, we can only define true frequency
with adaptive method, which would lead to quantify nonstationarity and
nonlinearity. Examples from classic nonlinear system and recent climate
change data will be used to illustrate the prowess of the new approach.
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