Useful links

Refereed publications

  • Mathis, S. M., Webber, A. E., León, T. M., Murray, E. L., Sun, M., White, L. A., Brooks, L. C., Green, A., Hu, A. J., Rosenfeld, R., Shemetov, D., Tibshirani, R. J., McDonald, D. J., Kandula, S., Pei, S., Yaari, R., Yamana, T. K., Shaman, J., Agarwal, P., Balusu, S., Gururajan, G., Kamarthi, H., Prakash, B. A., Raman, R., Zhao, Z., Rodríguez, A., Meiyappan, A., Omar, S., Baccam, P., Gurung, H. L., Suchoski, B. T., Stage, S. A., Ajelli, M., Kummer, A. G., Litvinova, M., Ventura, P. C., Wadsworth, S., Niemi, J., Carcelen, E., Hill, A. L., Loo, S. L., McKee, C. D., Sato, K., Smith, C., Truelove, S., Jung, S.-M., Lemaitre, J. C., Lessler, J., McAndrew, T., Ye, W., Bosse, N., Hlavacek, W. S., Lin, Y. T., Mallela, A., Gibson, G. C., Chen, Y., Lamm, S. M., Lee, J., Posner, R. G., Perofsky, A. C., Viboud, C., Clemente, L., Lu, F., Meyer, A. G., Santillana, M., Chinazzi, M., Davis, J. T., Mu, K., Piontti, A. P. Y., Vespignani, A., Xiong, X., Ben-Nun, M., Riley, P., Turtle, J., Hulme-Lowe, C., Jessa, S., Nagraj, V. P., Turner, S. D., Williams, D., Basu, A., Drake, J. M., Fox, S. J., Suez, E., Cojocaru, M. G., Thommes, E. W., Cramer, E. Y., Gerding, A., Stark, A., Ray, E. L., Reich, N. G., Shandross, L., Wattanachit, N., Wang, Y., Zorn, M. W., Aawar, M. A., Srivastava, A., Meyers, L. A., Adiga, A., Hurt, B., Kaur, G., Lewis, B. L., Marathe, M., Venkatramanan, S., Butler, P., Farabow, A., Ramakrishnan, N., Muralidhar, N., Reed, C., Biggerstaff, M., and Borchering, R. K. (2024) Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations. Nature Communications, 15, 6289.
  • Dey, T., Lee, J., Chakraborty, S., Chandra, J., Bhaskar, A., Zhang, K., Bhaskar, A., and Dominici, F. (2021) Lag time between state-level policy interventions and changepoints in COVID-19 outcomes in the United States. Patterns, 2, 100306.
  • Lee, M. and Lee, J. (2021) Long-term trend analysis of extreme coastal sea levels with changepoint detection. Journal of the Royal Statistical Society Series C: Applied Statistics, 70, 434-458.
  • Lee, M. and Lee, J. (2020) Trend and return level of extreme snow events in New York City. The American Statistician, 74, 282-293.
  • Lee, J., Lund, R., Woody, J., and Xu, Y. (2020) Trend assessment for daily snow depths with changepoint considerations. Environmetrics, 31, e2580.
  • Clark, P. E., Nielson, R. M., Lee, J., Ko, K., Johnson, D. E., Ganskopp, D. C., Chigbrow, J., Pierson, F. B., and Hardegree, S. P. (2017) Prescribed fire effects on activity and movement of cattle in mesic sagebrush steppe. Rangeland Ecology & Management, 70, 437-447.
  • Ashouri, H., Sorooshian, S., Hsu, K., Bosilovich, M. G., Lee, J., Wehner, M. F., and Collow, A. (2016) Evaluation of NASA's MERRA precipitation product in reproducing the observed trend and distribution of extreme precipitation events in the United States. Journal of Hydrometeorology, 17, 693-711.
  • Lee, J., Dini, A., and Negri, W. (2016) An efficient generalized least squares algorithm for periodic trended regression with autoregressive errors. Numerical Algorithms, 71, 59-75.
  • Clark, P. E., Lee, J., Ko, K., Nielson, R. M., Johnson, D. E., Ganskopp, D. C., Pierson, F. B., and Hardegree, S. P. (2016) Prescribed fire effects on resource selection by cattle in mesic sagebrush steppe. Part 2: Mid-summer grazing. Journal of Arid Environments, 124, 398-412.
  • Hughes, T. A. C. and Lee, J. (2015) A new test for short memory in long memory time series. The American Statistician, 69, 182-190.
  • Lee, J., Li, S., and Lund, R. (2014) Trends in extreme U.S. temperatures. Journal of Climate, 27, 4209-4225.
  • Clark, P. E., Lee, J., Ko, K., Nielson, R. M., Johnson, D. E., Ganskopp, D. C., Chigbrow, J., Pierson, F. B., and Hardegree, S. P. (2014) Prescribed fire effects on resource selection by cattle in mesic sagebrush steppe. Part 1: Spring grazing. Journal of Arid Environments, 100-101, 78-88.
  • Lee, J. and Lund, R. (2012) A refined efficiency rate for ordinary least squares and generalized least squares estimators for a linear trend with autoregressive errors. Journal of Time Series Analysis, 33, 312-324.
  • Lee, J. and Ko, K. (2009) First-order bias correction for fractionally integrated time series. The Canadian Journal of Statistics, 37, 476-493.
  • Lee, J. (2009) A reformulation of weighted least squares estimators. The American Statistician, 63, 49-55.
  • Ko, K., Lee, J., and Lund, R. (2008) Confidence intervals for long memory regressions. Statistics & Probability Letters, 78, 1894-1902.
  • Lee, J. and Lund, R. (2008) Equivalent sample sizes in time series regressions. Journal of Statistical Computation and Simulation, 78, 285-297.
  • Lee, J. and Ko, K. (2007) One-way analysis of variance with long memory errors and its application to stock return data. Applied Stochastic Models in Business and Industry, 23, 493-502.
  • Lee, J. and Lund, R. (2004) Revisiting simple linear regression with autocorrelated errors. Biometrika, 91, 240-245.
  • Park, Y. S. and Lee, J. (1996) A mixed randomized response technique. Journal of the Korean Statistical Society, 25, 39-48.