Marginal models for categorical data

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 Models for Categorical Data

Conceptual and Visual Models for Categorical Data

A dynamic conceptual model for categorical data is described that likens observations to gas molecules in a pressure chamber. In this physical model frequency corresponds to pressure, and fitting a statistical model by maximum likelihood corresponds to minimizing energy or balancing of forces. The model provides neat explanations of many results for categorical data, extends readily to multiway...

Categorical models for spatial data uncertainty

Considerable disparity exists between the current state of the art for categorical spatial data error modeling and the current state of the practice for reporting categorical data quality. On one hand, the general Monte Carlo simulation-based error propagation framework is a fixture in spatial data error handling; researchers have identified potentially powerful approaches to characterizing cat...

Testing Marginal Homogeneity for Ordinal Categorical Variables

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