James Long
Assistant Professor of Statistics
Texas A&M University, College Station

email: jlong + the at symbol + stat.tamu.edu
office: 406D Blocker

Research Interests

My research is focused on inference and prediction problems arising from astronomy data sets. Astrostatistics is characterized by complex data types, such as irregularly sampled vector valued functions, and multistage inference problems. Work on astronomy data sets has led to my methodological interests within statistics including frequency estimation for periodic signals, inference with approximate models, and classification with feature measurement error.

See below for a list of my publications and links to course websites. I also have a google scholar profile and code hosted on github under longjp.
  • Z. Lin and J.P. Long. Mixture Proportion Estimation for Positive-Unlabeled Learning. Submitted to Journal of Machine Learning Research, 2018+.
  • J.P. Long and R. F. Souza. Statistical Methods in Astronomy. Wiley StatsRef, 2018.
  • J.P. Long. A Note on Parameter Estimation for Misspecified Regression Models with Heteroskedastic Errors. Electronic Journal of Statistics, 2017.
  • W. Yuan, S. He, L. M. Macri, J.P. Long, J. Z. Huang The M33 Synoptic Stellar Survey. II. Mira Variables. The Astrophysical Journal, 2017.
  • B. Salmon, C. Papovich, J.P. Long, et al. Breaking the Curve with CANDELS: A Bayesian Approach to Reveal the Non-Universality of the Dust-Attenuation Law at High Redshift. The Astrophysical Journal, 2016.
  • S. He, W. Yuan, J.Z. Huang, J.P. Long, L.M. Macri. Period Estimation for Sparsely-sampled Quasi-periodic Functions Applied to Miras. The Astrophysical Journal, 2016.
  • J.P. Long, E. Chi, R. Baraniuk. Estimating a Common Period for a Set of Irregularly Sampled Functions with Applications to Periodic Variable Star Data. Annals of Applied Statistics, 2016.
  • J.P. Long, N. El Karoui, J.A. Rice. Kernel Density Estimation with Berkson Error. The Canadian Journal of Statistics, 2016.
  • N. Mondrik, J.P. Long, J. Marshall. A Multiband Generalization of the Analysis of Variance Period Estimation Algorithm and the Effect of Inter-band Observing Cadence on Period Recovery Rate. Astrophysical Journal Letters, 2015.
  • J.P. Long, N. El Karoui, J.A. Rice, J.W. Richards, J. Bloom. Optimizing Automated Classification of Variable Stars in New Synoptic Surveys. Publications of the the Astronomy Society of the Pacific, 2012.
  • A.N. Morgan, J.P. Long, J.W. Richards, T. Broderick, N.R. Butler, J.S. Bloom. Rapid, Machine-learned Resource Allocation: Application to High-redshift Gamma-Ray Burst Follow-up. The Astrophysical Journal, 2012.
  • J.P. Long , J.S. Bloom, N. El Karoui, J. Rice, and J.W. Richards. Classification of poorly time sampled light curves of periodic variable stars. Astrostatistics and Data Mining. Springer Series in Astrostatistics, 2012.
  • J.W. Richards, D.L. Starr, H. Brink, A.A. Miller, J.S. Bloom, N.R. Butler, J.B. James, J.P. Long, and J. Rice. Active learning to overcome sample selection bias: Application to photometric variable star classification. The Astrophysical Journal, 2011.

  • Statistics 689 - Statistical Computing with R and Python: Spring 2018
  • Statistics 611 - Theory of Statistics II: Spring 2018
  • Astrostatistics: Astrostatistics course taught Fall 2016 at SAMSI.
  • Statistics 689 - Astrostatistics: Astrostatistics course taught Fall 2015 at TAMU.
    Contact Information

    Email: jlong + the at symbol + stat.tamu.edu
    Address: Department of Statistics
    447 Blocker Building
    Texas A&M University
    College Station, TX 77843-3143 USA

    Last updated: February 15, 2018