SUMMARY Diagnostic residual and partial residual plots are proposed to identify nonlinearity in covariates for generalized linear models. It is shown that these plots are complement each other in the detection of nonlinearity. In addition, a transformed additive model which allows the resulting residual and partial residual plots to be obtained through the standard least squares approach is pro...

Causal calculus is a tool to express causal effects in the terms of observational probability distributions. The application of causal calculus in the non-parametric form requires only the knowledge of the causal structure. However, some kind of explicit modeling is needed when numeric estimates of the causal effect are to be calculated. In this paper, the estimation of complicated nonlinear ca...

We compare several accounting based models for bankruptcy prediction. The models are developed and tested on large data sets containing annual financial statements for Norwegian limited liability firms. Out-of-sample and out-of-time validation shows that generalized additive models significantly outperform popular models like linear discriminant analysis, generalized linear models and neural ne...

where x ∈ R denotes a sample and xj ∈ R denotes the j-th explanatory variable for each j ∈ [1, p] , {j ∈ N|1 ≤ j ≤ p}. This was first proposed by Hastie and Tibshirani (1987) and is known as a generalized additive model (GAM). In this paper, we call fj(·) a weight function and f(·) a GAM predictor. This not only includes linear predictors but also captures nonlinear relationships between explan...

Recent work by Reiss and Ogden (2009) provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross validation (GCV) for smoothing parameter selection in semiparametric regression. However, existing REML or marginal likelihood (ML) based methods for semiparametric GLMs use iterative REML/ML estimation of the smoothing parameters of working linea...

We investigate a generalized stochastic model with the property known as mean reversion, that is, the tendency to relax towards a historical reference level. Besides this property, the dynamics is driven by multiplicative and additive Wiener processes. While the former is modulated by the internal behavior of the system, the latter is purely exogenous. We focus on the stochastic dynamics of vol...

13 Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a widely used 14 approach to study protein-DNA interactions. To analyze ChIP-Seq data, practitioners are 15 required to combine tools based on different statistical assumptions and dedicated to spe16 cific applications such as calling protein occupancy peaks or testing for differential occu17 pancies. Here, we present Ge...

Let R be a 2-torsion free ring and L a Lie ideal of R. An additive mapping F : R ! R is called a generalized derivation on R if there exists a derivation d : R to R such that F(xy) = F(x)y + xd(y) holds for all x y in R. In the present paper we describe the action of generalized derivations satisfying several conditions on Lie ideals of semiprime rings.

Emotion research has long been dominated by the "standard method" of displaying posed or acted static images of facial expressions of emotion. While this method has been useful, it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correc...