This paper is concerned with estimating the mean of a random variable Y conditional on a vector of covariates X under weak assumptions about the form of the conditional mean function. Fully nonparametric estimation is usually unattractive when X is multidimensional because estimation precision decreases rapidly as the dimension of X increases. This problem can be overcome by using dimension red...

Projection pursuit regression (PPR) can be used to estimate a smooth function of several variables from noisy and scattered data. The estimate is a sum of smoothed one-dimensional projections of the variables. This paper discusses an extension of PPR to exponential family distributions, called generalized projection pursuit regression (GPPR). The proposed model allows multiple responses and non...

Statistical models of the realized niche of species are increasingly used, but systematic comparisons of alternative methods are still limited. In particular, only few studies have explored the effect of scale in model outputs. In this paper, we investigate the predictive ability of three statistical methods (generalized linear models, generalized additive models and classification tree analysi...

Logistic regression1 has been widely used in direct marketing applications to develop response and conversion models. Although attractively simple, logistic regression has been criticized for failing to capture the nonlinearity, and therefore possibly not leading to satisfactory results. Introduced by Hastie and Tibshirani, Generalized Additive Model2 (GAM) provides the ability to detect the no...

We develop a non-parametric cost function using generalized additive models and demonstrate how to test for input separability. Our empirical example focuses on Canadian cable television (CATV) provision. We estimate a new non-parametric cost function for this industry using financial and operating data collected between 1990 and 1996. This period is of particular importance from a policy persp...

Single-site recreation demand and dichotomous choice contingent valuation analyses are typically conducted by implementing models containing strong parametric assumptions, which are rarely underpinned by theoretical arguments. This work illustrates how these assumptions can be relaxed and the estimation conducted semiparametrically by using generalized additive models (GAMs). This approach dire...

Event-Related Potential (ERP) signals obtained from EEG recordings are widely used for studying cognitive processes in spoken language processing. The computation of ERPs involves averaging over multiple participants and multiple stimuli. Especially with speech stimuli, which also evoke substantial exogenous excitation, even averaging within conditions results in pooling many sources of varianc...

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs /GAMs modeling: from species distribution to environmental management , held in Riedera...

We consider the estimation of credit scores by means of semiparametric logit models. In credit scoring, the fitted rating score shall not only provide an optimal classification result but serves also as a modular component of a (typically quite complex) rating system. This means in particular that a rating score should be given by a linearly weighted sum of rating factors. That way the rating p...