Abstract To build a forecasting tool for the state of eutrophication in Archipelago Sea, we fitted Generalized Additive Mixed Model (GAMM) to marine environmental monitoring data, which were collected over years 2011–2019 by an automated profiling buoy at Seili ODAS-station. The resulting “Seili-index” can be used predict chlorophyll- α (chl-a) concentration seawater number days ahead using tem...

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...

PURPOSE Competing risks observations, in which patients are subject to a number of potential failure events, are a feature of most clinical cancer studies. With competing risks, several modeling approaches are available to evaluate the relationship of covariates to cause-specific failures. We discuss the use and interpretation of commonly used competing risks regression models. EXPERIMENTAL D...

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...

A common design in social psychology involves the use of two independent variables, an experimental manipulation and a measured individual difference, and the interest is in the interaction between them. In such designs, there are often obvious covariate(s), correlated with the measured independent variable, which the researcher wishes to control. Typically this is done by including the covaria...

Missing covariate values is a common problem in a survival data research. The aim of this study is to compare the use of the multiple imputation (MI) and last observation carried forward (LOCF) methods for handling missing covariate values in the Cox proportional hazards (PH) regression model. The comparisons between the methods are based on simulated data. The missingness mechanism is assumed ...

This paper presents a simulation study to investigate the behavior of estimates of covariate effects in a Bayesian hierarchical changepoint model. The model is a segmented linear regression model with one changepoint within a fully Bayesian framework. We introduce covariate effects into the model in three ways: as an affect on the interaction term, an affect on the slope after the changepoint, ...

New approaches to expedite the development of safe and effective pediatric dosing regimens and first-in-child doses are urgently needed. Model-based approaches require quantitative functions on the maturation of different metabolic pathways. In this study, we directly incorporated a pediatric covariate model for the glucuronidation of morphine into a pediatric population model for zidovudine gl...