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...

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 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 Grubbs' measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have...

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...

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...