Statistics and Data Science Seminar
Jennifer Pajda-Delao / Julien Leider
University of Illinois at Chicago
Persistence of a Swamp Rabbit Metapopulation: The Incidence Function Model Approach / A Quantile Regression Study of Climate Change in Chicago
Abstract: Jennifer's Abstract:
We evaluate the status and distribution of swamp rabbits (Sylvilagus
aquaticus) in Missouri using the Incidence Function Model and logistic
regression in an effort to assess the long term viability of the
Missouri metapopulation. We used results of latrine surveys performed
in 1992 and 2001 to estimate the likelihood of persistence of swamp
rabbits over periods of 9 to 1000 years. Under current conditions, more
than 50% of the patches are predicted to contain rabbits after 1000
years. Logistic regression revealed that both patch area and patch
isolation were significantly related to patch occupancy, and play key
roles in the incidence of swamp rabbits.
Julien's Abstract:
This study uses quantile regression combined with time series methods to
analyze change in temperatures in Chicago during the period 1960-2010.
It builds on previous work in applying quantile regression methods to
climate data by Timofeev and Sterin (2010) and work by the Chicago Climate
Task Force on analyzing climate change in Chicago. We use data from the
Chicago O'Hare Airport weather station archived by the National Climatic
Data Center to look at changes in weekly average temperatures. We use the
method described by Xiao et al. (2003) to remove autocorrelation in the
data, the rank-score method with IID assumption to calculate confidence
intervals, and nonparametric local linear quantile regression to estimate
temperature trends. We find that the decade 1960-1969 was significantly
cooler than later decades around the middle of the yearly seasonal
cycle at both the median and 95th percentile of the temperature
distribution. However, we do not find a significant change across later
decades of the study period.
Wednesday February 29, 2012 at 4:00 PM in SEO 636