Identification of a nonlinear additive system is considered. An input signal is designed in such a way that the problem of identification of nonlinear additive systems is reduced to a problem of identification of static nonlinear functions. Then, three approaches are established to estimate the order of the system. The methods exploit the structure of the nonlinear additive model so that their ...

Condition Based Maintenance Using Proportional Hazards Model

The lme4 package uses sparse matrix technology and clever decompositions of the likelihood to fit linear, generalized, and nonlinear mixed-effects models. The amer package extends lme4’s scope to include generalized additive mixed models (GAMM). This vignette summarizes the main ideas behind additive models and their representation in the form of a mixed model, describes the modifications to lm...

We explore additive models that combine both parametric and nonparamet-ric terms and propose a p n-consistent backktting estimator for the parametric component of the model. The theoretical properties of the estimator are developed for the case with a single nonparametric term and extended to an arbitrary number of nonparametric additive terms. An estimator for the optimal band-width making min...

The Cox proportional hazards (PH) model with time-dependent covariates (referred to as the extended PH model) has been widely used in medical and health related studies to investigate the effects of time-varying risk factors on survival. Theories and practices regarding model estimation and fitting have been well developed for the extended PH model. However, little has been done regarding sampl...

The perception of prosodic prominence is influenced by different sources like different acoustic cues, linguistic expectations and context. We use a generalized additive model and a random forest to model the perceived prominence on a corpus of spoken German. Both models are able to explain over 80% of the variance. While the random forests give us some insights on the relative importance of th...