Estimation and prediction for probability distribution functions and/or quantiles
for dependent data; modeling space-time dependencies of environmental processes
Description of Current Research
Modeling pdf's and/or quantiles for dependent data. I am developing
algorithms for direct quantile estimation for nonstationary time series, and
investigate possible extensions to the spatial and space-time cases.
Space-time models for dependent data. I am currently working on two
air pollution projects: prediction of daily ground-level ozone at the ZIP-code
level in Chicago, and space-time modeling of daily PM10 in Northern Italy.
Parametric simulation, bootstrap techniques. I am investigating
parametric simulation methods in the space-time setting. Preliminary results show
that this approach improves the accuracy of predictions obtained by space-time
interpolation with estimated parameters.
Student
Background Knowledge and Skills
Required Skills: very good programming skills, knowledge of basic
statistical methods, reliability
Desirable: exposure to one or more of the following areas of
Mathematics and Statistics: time series analysis, numerical methods, multivariate
analysis, spatial statistics, smoothing techniques
Expected Responsibilities
Data management: basic summaries, imputation of missing values,
presentation of results; literature reviews
Expected Benefits
Aquire experience in handling large data sets and programming skills; learn new
statistical methods; develop broader thinking about complex problems, understand
practical issues in conducting multidisciplinary research.
Last updated: April 4, 2005
To contact us:
Gender Equity Project
509 Thomas Hunter Hall
Department of Psychology
Hunter College of the City University of New York
695 Park Avenue
New York, NY 10021
This website was created and designed
by Monica Hopenwasser and Jocelyn Tan with assistance from
interns Shirley Wong, Tina Lau, Brock Fansler and Rommel Genciana.
