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- Caragea, Petruţa C., et al. Show all 5 Authors
- Journal of agricultural, biological, and environmental statistics 2019 v.24 no.1 pp. 1-25
- Bayesian theory; climate; growing season; linear models; phenology; spatial data; time series analysis; uncertainty; vegetation; vegetation index; weather; India
- ... Estimating the timing of the occurrence of events that characterize growth cycles in vegetation from time series of remote sensing data is desirable for a wide area of applications. For example, the timings of plant life cycle events are very sensitive to weather conditions and are often used to assess the impacts of changes in weather and climate. Likewise, understanding crop phenology can have a ...
- Caragea, Petruţa C., et al. Show all 2 Author
- Journal of agricultural, biological, and environmental statistics 2014 v.19 no.4 pp. 451-469
- confidence interval; covariance; epidemiology; forestry; models; prediction; regression analysis; scientists; soil science; uncertainty; vegetation; Midwestern United States
- ... Spatially structured discrete data arise in diverse areas of application, such as forestry, epidemiology, or soil sciences. Data from several binary variables are often collected at each location. Variation in distributional properties across the spatial domain is of interest. The specific application that motivates our work involves characterizing historical distributions of two species of Oak in ...