Nonlinear Models for Longitudinal Data

Nonlinear mixed effects models for longitudinal 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 ...

Functional Nonlinear Mixed Effects Models for Longitudinal Image Data

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FNMEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual tra...

Transition Models for Analyzing Longitudinal Data with Bivariate Mixed Ordinal and Nominal Responses

In many longitudinal studies, nominal and ordinal mixed bivariate responses are measured. In these studies, the aim is to investigate the effects of explanatory variables on these time-related responses. A regression analysis for these types of data must allow for the correlation among responses during the time. To analyze such ordinal-nominal responses, using a proposed weighting approach, an ...

A New Nonparametric Regression for Longitudinal Data

In many area of medical research, a relation analysis between one response variable and some explanatory variables is desirable. Regression is the most common tool in this situation. If we have some assumptions for such normality for response variable, we could use it. In this paper we propose a nonparametric regression that does not have normality assumption for response variable and we focus ...