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I was drawn to the discipline of statistics by a fascination with randomness, and by the way it blends mathematics and scientific content. I have enjoyed interactions with researchers in many areas, especially the natural sciences, which have given me opportunities to learn about these fields and to make contributions to them. Underlying these separate analyses are paradigms of statistical methodology that have been developed over the last 100 years. This evolution accelerates as statisticians confront new challenges in the information age. |
I am especially interested in formulating
methods for analyzing data that arise in the form of random functions, such as time
series, and which involve large quantities of data and computationally intensive analysis.
Much of my recent work has centered around two projects in astronomy: detecting objects in the outer regions of the solar system (the Kuiper Belt) and detecting gamma-ray pulsars. Small bodies with radii >100 km have recently been detected beyond Neptune using
large telescopes. The purpose of the Taiwanese American
Occultation Survey (TAOS) is to measure directly the number
of these objects (KBO's) down to the typical size of cometary nuclei (a few km).
When a KBO moves in between the earth and a distant star it will block the starlight
momentarily. A telescope monitoring the starlight will thus see it blinking. The
probability of such occultation events is so low that it will be necessary to conduct 100
billion measurements per year in order to detect the ten to four thousand such occultation
events expected. Thus, foremost among the statistical problems is the necessity of
developing methods to detect very rare, faint events in very large quantities of data.
A gamma-ray pulsar is a rotating neutron star that emits gamma-ray photons. A statistical challenge is to infer from a sequence of arrival times of such photons, whether the source is periodic, corresponding to a pulsar, or whether it is constant, corresponding to background radiation.
Some Recent Papers
Nicolai Meinshausen, Peter Bickel & John Rice (2007). Efficient Blind Search: Optimal Power of Detection under Computational Cost Constraints. [Abstract, PDF]
Peter Bickel, Bas Kleijn, & John Rice (2007). Event Weighted Tests for Detecting Periodicity in Photon Arrival Times. [Abstract, PDF]
Peter Bickel, Bas Kleijn, & John Rice (2006). On Detecting Periodicity in Astronomical Point Processes. [Abstract, PDF]
Nicolai Meinshausen & John Rice
(2004) Estimating the Proportion of False Null Hypotheses among a Large Number of
Independently Tested Hypotheses. [abstract pdf]
Young Cho and John Rice (2004).
Estimating velocity fields on a freeway from low resolution video. [ abtract pdf ]
Peter Bickel, Chao Chen, Jaimyoung
Kwon, John Rice, Erik van Zwet and Pravin Varaiya (2004). Measuring Traffic. [abstract pdf]
John Rice (2003). Functional and
longitudinal data analysis: perspecptives on smoothing. [abstract
pdf]. (Keynote address at the conference Emerging Issues in Longitudinal Data Analysis.).
To appear in Statistica Sinica.
Chyng-Lan Liang, John Rice, Imke de
Pater, Charles Alcock, Tim Axelrod, Andrew Wang, and Stuart Marshall. (2002).
Statistical methods for detecting occultations by Kuiper belt objects: the
Taiwanese-American occultation survey. [abstract pdf] To appear in Statistical Science.
Peter Bickel, Chao Chen, Jaimyoung
Kwon, John Rice, Pravin Varaiya and Erik van Zwet (2001). Traffic flow on a freeway
network. [pdf] To appear in the Proceedings of a workshop on
Nonlinear Estimation and Classification, Mathematical Sciences Research Institute.
John Rice (2001). Reflections on SCMA
III. [postscript, pdf]. To appear
in Statistical Challenges in Modern Astronomy III.
Leo Breiman, Michael Last, and John
Rice (2001). Random forests: finding quasars. [postscript, pdf] To appear in Statistical Challenges in Modern Astronomy
III.
Xiaoyan Zhang and John Rice (2001).
Short term travel time predicting using a time-varying coefficient linear model. [pdf]
Erik van Zwet and John Rice (2001).
A simple and effective method of predicting travel times on freeways. [pdf]
Peter Hall, James Reimann,
and John Rice (2000). Nonparametric estimation of a periodic function. Biometrika 87,
545-557. [abstract]
K.F. Petty, P.J. Bickel, J. Kwon, M.
Ostland, and J. Rice (1999) A new methodology for evaluating incident detection
algorithms. [abstract]
[paper: postscript]
John Rice and Colin Wu (2001).
Nonparametric mixed effects models for unequally sampled noisy curves. Biometrics 57,
253-259. [abstract ]
Ken Newman and John Rice
(1998). Statistical model for survival of Chinook salmon smolts outmigrating through
the lower Sacramento-San Joaquin system. Interagency Ecological Program for the San
Francisco Bay/Delta Estuary, Technical Report 59. [abstract]
.[paper: compressed postscript, pdf]
Donald R. Fredkin and John Rice (2001) Fast
evaluation of the likelihood of an HMM: ion channel currents with filtering and colored
noise IEEE Transactions on Signal Processing 49, 625-633 [abstract ] [paper (pdf)]
Babette A. Brumback and John Rice. (1998)
Smoothing spline models for the analysis of nested and crossed samples of curves.
Journal of the American Statistical Association 93, 961-976 [abstract
]
Donald Hoover, John Rice, Colin Wu, and Li-Ping
Yang. (1998) Nonparametric smoothing estimates of time-varying coefficient models with
longitudinal data. Biometrika 85, 809-822. [abstract ]