The aim of this paper is to introduce generalized symmetric linear models (GSLMs) in the same sense of generalized linear models (GLMs), in which a link function is defined to establish a relationship between the mean values of symmetric distributions and linear predictors. The class of...

We propose a linear regression model with slash-elliptical errors. The slash-elliptical distribution with parameter q is defined as the ratio of two independent random variables Z and U1q, where Z has elliptical distribution and U has uniform distribution in (0,1). The main feature of the...

This paper proposes a general definition of residuals for Birnbaum–Saunders nonlinear regression models by studying their statistical properties analytically and using Monte Carlo experiments. Also, some diagnostic procedures are derived based on case-deletion and mean-shift outlier models...

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo <italic>et al.</italic> 22 by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a...

The aim of this paper is to derive diagnostic procedures based on case-deletion model for symmetrical nonlinear regression models, which complements Galea et al. (2005) that developed local influence diagnostics under some perturbation schemes. This class of models includes all symmetric...

In this work we present theoretical details of a general residual for symmetric nonlinear regression models. This class of models includes all symmetric continuous distributions such as normal, Student-t, Pearson VII, power exponential and logistic. Such regression models are used for the...

We discuss in this paper heteroscedastic linear models with symmetrical errors. The symmetrical class includes all symmetrical continuous distributions such as normal, Student-t, power exponential, logistics I and II, contaminated normal, so on. The variety of error distributions with different...

In this paper, we discuss the extension of some diagnostic procedures to symmetrical nonlinear regression models. This class provides a useful generalization of normal nonlinear regression models since the location parameter continues to be the mean (when it exists) and the error distributions...