A Bayesian approach to Lagrangian data assimilation

A Bayesian approach to Lagrangian data assimilation

Lagrangian data arise from instruments that are carried by the flow in a fluid field. Assimilation of such data into ocean models presents a challenge due to the potential complexity of Lagrangian trajectories in relatively simple flow fields. We adopt a Bayesian perspective on this problem and thereby take account of the fully non-linear features of the

A Bayesian Approach to Data Assimilation

Data assimilation is formulated in a Bayesian context. This leads to a sampling problem in the space of continuous time paths. By writing down a density in path space, and conditioning on observations, it is possible to define a range of Markov Chain Monte Carlo (MCMC) methods which sample from the desired distribution in path space, and thereby solve the data assimilation problem. The basic bu...

A Forward Sensitivity Approach to Lagrangian Data Assimilation

The main goal is to show that the FSM is appropriate for assimilating Lagrangian data into non-linear models. Lagrangian instruments are a popular tool for providing measurements of fluid dynamics and transport properties. The dynamics of the ocean processes that ”create” the Lagrangian data collected by ocean drifters are often modeled as highly non-linear processes. This nonlinearity leads to...

a new approach to credibility premium for zero-inflated poisson models for panel data

هدف اصلی از این تحقیق به دست آوردن و مقایسه حق بیمه باورمندی در مدل های شمارشی گزارش نشده برای داده های طولی می باشد. در این تحقیق حق بیمه های پبش گویی بر اساس توابع ضرر مربع خطا و نمایی محاسبه شده و با هم مقایسه می شود. تمایل به گرفتن پاداش و جایزه یکی از دلایل مهم برای گزارش ندادن تصادفات می باشد و افراد برای استفاده از تخفیف اغلب از گزارش تصادفات با هزینه پائین خودداری می کنند، در این تحقیق ...

Bayesian data assimilation