Julie McIntyre

Julie McIntyre

2006  |  Associate Professor of Statistics
North Carolina State University 2003, PhD
CH 201D   |   907-474-7772
jpmcintyre@alaska.edu


My research is in the area of nonparametric statistical methods. In general, nonparametric methods aim to estimate a function from data under minimal assumptions about either the distribution of the data or the form of the function. Within this broad field, my research efforts have focused on the two specific areas of measurement error models and spatial smoothers. In addition, I often collaborate with subject-area scientists and students at UAF. These collaborations have led to a number of interesting applied research projects in fields such as biology, ecology and education.

Highlighted works:

Barry, R. P. and McIntyre, J. (2020). Lattice-based methods for regression and density estimation on complicated multidimensional regions. Environmental and Ecological Statistics, 27, 571 – 589.

McIntyre, J. and Barry, R. (2018). A lattice-based smoother for regions with irregular boundaries and holes. Journal of Computational and Graphical Statistics, 27, 360 – 367.

McIntyre, J. Johnson, B.A. and Rappaport, S.M. (2018). Monte Carlo methods for nonparametric regression with heteroscedastic measurement error. Biometrics, 74, 498 – 505.

Smith, J.*, Karpovich, S., Horstman, L. A., McIntyre, J., O’Brian, D. M. (2019) Seasonal differences in foraging and isotopic niche width related to body size in Gulf of 91ÊÓƵ harbor seals. Canadian Journal of Zoology, 97, 1156–1163.

*denotes UAF graduate students