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- Johnson, Margaret; Caragea, Petruţa C.; Meiring, Wendy; Jeganathan, C.; Atkinson, Peter M.
- 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 ...
- Tadayon, Vahid; Rasekh, Abdolrahman
- Journal of agricultural, biological, and environmental statistics 2019 v.24 no.1 pp. 49-72
- Bayesian theory; Markov chain; Monte Carlo method; environmental science; geostatistics; nitrates; normal distribution; spatial data; statistical inference; statistical models; variance covariance matrix
- ... Spatial models based on the Gaussian distribution have been widely used in environmental sciences. However, real data could be highly non-Gaussian and may show heavy tails features. Moreover, as in any type of statistical models, in spatial statistical models, it is commonly assumed that the covariates are observed without errors. Nonetheless, for various reasons such as measurement techniques or ...