Motivated by a nonparametric GARCH model we consider nonparametric additive autoregression models in the special case that the additive components are linked parametrically+We show that the parameter can be estimated with parametric rate and give the normal limit+ Our procedure is based on two steps+ In the first step nonparametric smoothers are used for the estimation of each additive componen...

We consider the problem of predicting an outcome variable using p covariates that are measured on n independent observations, in a setting in which additive, flexible, and interpretable fits are desired. We propose the fused lasso additive model (FLAM), in which each additive function is estimated to be piecewise constant with a small number of adaptively-chosen knots. FLAM is the solution to a...

Li, Fine, and Brookhart (2015) presented an extension of the two-stage least squares (2SLS) method for additive hazards models which requires an assumption that the censoring distribution is unrelated to the endogenous exposure variable. We present another extension of 2SLS that can address this limitation.

We propose a class of transformation hazard models for rightcensored failure time data. It includes the proportional hazards model (Cox) and the additive hazards model (Lin and Ying) as special cases. Due to the requirement of a nonnegative hazard function, multidimensional parameter constraints must be imposed in the model formulation. In the Bayesian paradigm, the nonlinear parameter constrai...

With the passage of time the impacts of natural hazards continue to increase around the world. The globalization and growth of human societies and their escalating complexity and river flooding will further increase the risks of natural hazards. Flood prediction and control are one of the greatest challenges facing the world today, which have become more frequent and severe due to the effects o...

Lean manufacturing, which establishes small production "cells," or teams of workers, who complete an entire product from raw material processing through final assembly and shipment, increases health and safety hazards by mixing previously separated exposures to various chemicals (with possible additive and cumulative effects) and noise. The intensification of work leads to greater ergonomic and...

With the increasing availability of observational data from different sources at a global level, joint analysis of these data is becoming especially attractive. For such an analysis – oftentimes with little prior knowledge about local and global interactions between the different observational variables at hand – an exploratory, data-driven analysis of the data may be of particular relevance. I...

In this paper, we use a novel duration model to study joint retirement in married couples using the Health and Retirement Study. Whereas conventionally used models cannot account for joint retirement, our model admits joint retirement with positive probability and nests the traditional proportional hazards model. In contrast to other statistical models for simultaneous durations, it is based on...

Recurrent events analysis plays an important role in many applications, including the study of chronic diseases or recurrence infections. Historically, models for recurrent have been variants Cox model. In this article we introduce and describe application piece-wise exponential Additive Mixed Model (PAMM) illustrate how PAMMs can be used to flexibly model dependencies data. Simulations confirm...