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Statistical Programs
College of Agricultural
and Life Sciences
University of Idaho
Seminar Announcement
"Applied Statistics in Agriculture"
Change-point analysis of annual mean precipitation for northern, tropical and southern latitudes of the globe in the past century

Presented By
Dr. Venkata K. Jandhyala
Department of Mathematics
Washington State University

Tuesday, March 6
3:30 P. M.
Ag. Science 62

      Applying methods of change-point analysis, a statistical study of the annual mean precipitation from northern, tropical and southern latitudes of the globe is carried out based upon data for the past 100 years. The change-point analysis assumes multivariate Gaussianity for the time-series data, thus allowing spatial correlations between the three latitudes. The analysis, which aims to identify prevailing changes in the mean vector of the three-variate precipitation series, further assumes that the variance-covariance structure is stationary throughout the century, and that the data is independent over time. Recently developed change detection and change-point estimation methods for multivariate Gaussian data are applied to analyze the data. A simulation study is carried out in a bivariate set-up to investigate the robustness of the estimation methodology for deviation from Gaussianity as well as its sensitivity to estimation of the model parameters. Results from the simulation study are promising in the sense that the change-point mle is robust to deviations from Gaussianity and also the limiting distribution is unaltered by replacing known parameters by their estimates. Data analysis indentifies a significant change in the precipitation from northern and southern latitudes subsequent to the year 1944, whereas no change was identified in the data from tropical latitude. The discussion suggests that the change found in the data from northern and southern latitudes may not have been entirely due to gauge changes introduced in and around 1950.
All interested faculty, staff, and graduate students are invited to attend.


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