Selecting and fitting graphical chain models to longitudinal data

Fitting Models to Grouped Data

Fitting Graphical Interaction Models to Multivariate Time Series

Graphical interaction models have become an important tool for analysing multivariate time series. In these models, the interrelationships among the components of a time series are described by undirected graphs in which the vertices depict the components while the edges indictate possible dependencies between the components. Current methods for the identification of the graphical structure are...

Graphical simulation using chain models

This paper presents an extension of a previously described framework for the speci cation and manipulation of models of systems. This extension is particularly useful in the context of graphical simulation. The original framework and its extension include a convenient Application Programming Interface (API), and this paper provides examples of the use of this API in the context of graphical sim...

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 ...

Fitting models to data: Accuracy, Speed, Robustness

In vision and machine learning, almost everything we do may be considered to be a form of model fitting. Whether estimating the parameters of a convolutional neural network, target tracking, computing low-dimensional representations of datasets, computing structure and motion from image collections, estimating parameters for an inference model such as Markov random fields, or pretty much anythi...