Modelling Bird Migration with Motus Data and Bayesian State-Space Models
نویسندگان
چکیده
منابع مشابه
Analysis of Hierarchical Bayesian Models for Large Space Time Data of the Housing Prices in Tehran
Housing price data is correlated to their location in different neighborhoods and their correlation is type of spatial (location). The price of housing is varius in different months, so they also have a time correlation. Spatio-temporal models are used to analyze this type of the data. An important purpose of reviewing this type of the data is to fit a suitable model for the spatial-temporal an...
متن کاملBayesian Inference for Spatial Beta Generalized Linear Mixed Models
In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...
متن کاملBayesian Modelling of Outstanding Liabilities Incorporating Claim Count Uncertainty Bayesian Modelling of Outstanding Liabilities Incorporating Claim Count Uncertainty
This paper deals with the prediction of the amount of outstanding claims that an insurance company will pay in the near future. We consider various competing models using Bayesian theory and Markov chain Monte Carlo methods. Claim counts are used in order to add a further hierarchical stage in the usual log-normaland state-space models. By this way, we incorporate information from both the outs...
متن کاملA review of Bayesian state-space modelling of capture-recapture-recovery data.
Traditionally, state-space models are fitted to data where there is uncertainty in the observation or measurement of the system. State-space models are partitioned into an underlying system process describing the transitions of the true states of the system over time and the observation process linking the observations of the system to the true states. Open population capture-recapture-recovery...
متن کاملBayesian Forecasting
Bayesian Forecasting encompasses statistical theory and methods in time series analysis and time series forecasting, particularly approaches using dynamic and state space models, though the underlying concepts and theoretical foundation relate to probability modelling and inference more generally. This entry focuses speciically in the time series and dynamic modelling domain, with mention of re...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017