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Università della Svizzera italiana

Robust inference

Ronchetti, Elvezio

In: International encyclopedia of statistical science, 2011, p. 1240-1242

Università della Svizzera italiana

Saddlepoint test in measurement error models

Ma, Yanyuan ; Ronchetti, Elvezio

In: Journal of the American statistical association, 2011, vol. 106, no. 493, p. 147-156

We develop second order hypothesis testing procedures in functional measurement error models for small or moderate sample sizes, where the classical first order asymptotic analysis often fails to provide accurate results. In functional models no distributional assumptions are made on the unobservable covariates and this leads to semiparametric models. Our testing procedure is derived using...

Università della Svizzera italiana

Variable selection in additive models by nonnegative garrote

Cantoni, Eva ; Mills Flemming, Joanna ; Ronchetti, Elvezio

In: Statistical modelling, 2011, vol. 11, no. 3, p. 237-252

We adapt Breiman’s (1995) nonnegative garrote method to perform variable selection in nonparametric additive models. The technique avoids methods of testing for which no general reliable distributional theory is available. In addition it removes the need for a full search of all possible models, something which is computationally intensive, especially when the number of variables is...

Università della Svizzera italiana

Robust and accurate inference for generalized linear models

Lô, Serigne N. ; Ronchetti, Elvezio

In: Journal of multivariate analysis, 2009, vol. 100, no. 9, p. 2126-2136

In the framework of generalized linear models, the nonrobustness of classical estimators and tests for the parameters is a well known problem and alternative methods have been proposed in the literature. These methods are robust and can cope with deviations from the assumed distribution. However, they are based on ¯rst order asymptotic theory and their accuracy in moderate to small samples...

Università della Svizzera italiana

General saddlepoint approximations of marginal densities and tail probabilities

Gatto, Riccardo ; Ronchetti, Elvezio ; della Svizzera italiana, Svizzera

In: Journal of the American statistical association, 1996, vol. 91, no. 434, p. 666-673

Saddlepoint approximations of marginal densities and tail probabilities of general nonlinear statistics are derived. They are based on the expansion of the statistic up to the second order. Their accuracy is shown in a variety of examples, including logit and probit models and rank estimators for regression.

Università della Svizzera italiana

Indirect robust estimation of the short-term interest rate process

Czellara, Veronika ; Karolyib, G. Andrew ; Ronchetti, Elvezio

In: Journal of Empirical Finance, 2007, vol. 14, no. 4, p. 546-563

We propose Indirect Robust Generalized Method of Moments (IRGMM), a simulationbased estimation methodology, to model short-term interest rate processes. The primary advantage of IRGMM relative to classical estimators of the continuous-time short-rate diffusion processes is that it corrects both the errors due to discretization and the errors due to model misspecification. We apply this approach...

Università della Svizzera italiana

Saddlepoint approximations for multivariate M -estimates with applications to bootstrap accuracy

Field, Chris ; Robinson, John ; Ronchetti, Elvezio

In: Annals of the Institute of Statistical Mathematics, 2008, vol. 60, no. 1, p. 205-224

We obtain marginal tail area approximations for the one-dimensional test statistic based on the appropriate component of the M-estimate for both standardized and Studentized versions which are needed for tests and confidence intervals. The result is proved under conditions which allow the application to finite sample situations such as the bootstrap and involves a careful discretization with...

Università della Svizzera italiana

Estimation of generalized linear latent variable models

Huber, Philippe ; Ronchetti, Elvezio ; Victoria-Feser, Maria-Pia

In: Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2004, vol. 66, no. 4, p. 893–908

Generalized Linear Latent Variable Models (GLLVM), as defined in Bartholomew and Knott (1999) enable modelling of relationships between manifest and latent variables. They extend structural equation modelling techniques, which are powerful tools in the social sciences. However, because of the complexity of the log-likelihood function of a GLLVM, an approximation such as numerical integration must...

Università della Svizzera italiana

Robust inference for generalized linear models

Cantoni, Eva ; Ronchetti, Elvezio

In: Journal of the American Statistical Association, 2001, vol. 96, no. 455, p. 1022-1030

By starting from a natural class of robust estimators for generalized linear models based on the notion of quasi-likelihood, we de¯ne robust deviances that can be used for stepwise model selection as in the classical framework. We derive the asymptotic distribution of tests based on robust deviances and we investigate the stability of their asymptotic level under contamination. The binomial and...

Università della Svizzera italiana

Saddlepoint approximations and tests based on multivariate M-estimates

Robinson, J. ; Ronchetti, Elvezio ; Young, G. A.

In: The Annals of Statistics, 2003, vol. 31, no. 4, p. 1154-1169

We consider multidimensional M-functional parameters defined by expectations of score functions associated with multivariate M-estimators and tests for hypotheses concerning multidimensional smooth functions of these parameters. We propose a test statistic suggested by the exponent in the saddlepoint approximation to the density of the function of the M-estimates. This statistic is analogous to...