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.
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 Alaska harbor seals. Canadian Journal of Zoology, 97, 1156–1163.
*denotes UAF graduate students