Browsing DiSES Working Papers by Author "Giordano, Francesco"
Now showing items 1-6 of 6
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A locally adaptive bandwidth selector for kernel based regression
Giordano, Francesco; Parrella, Maria Lucia (2009)The selection of the smoothing parameter represents a crucial step in the local polynomial regression, because of the implications on the consistency of the nonparametric regression estimator and because of the difficulties ... -
Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property
Giordano, Francesco; Parrella, Maria Lucia (2014)The local polynomial estimator is particularly affected by the curse of di- mensionality. So, the potentialities of such a tool become ineffective for large dimensional applications. Motivated by this, we propose a new ... -
GRID for model structure discovering in high dimensional regression
Giordano, Francesco; Lahiri, Soumendra Nath; Parrella, Maria Lucia (2014)Given a nonparametric regression model, we assume that the number of covariates d → ∞ but only some of these covariates are relevant for the model. Our goal is to identify the relevant covariates and to obtain some ... -
Parameter estimation in continuous stochastic volatility models
Albano, Giuseppina; Giordano, Francesco; Perna, Cira (2009)Continuous-time di usion processes are often used in literature to model dynamics of nancial markets. In such kinds of models a rel- evant role is played by the variance of the process. So assumptions on the functional ... -
Weak consistent moving block bootstrap estimator for the variance of CLS estimators in a class of bilinear models
Giordano, Francesco (2008)Grahn (1995) introduced the Conditional Least Squares estimators for the class (I) of bilinear models. These estimators have a variance which is difficulty to derive analytically. In this paper we derive the conditions ... -
Weak consistent moving block bootstrap estimator of sampling distribution of CLS estimators in a class of bilinear models
Giordano, Francesco (2005)Grahn, (1995) introduced the Conditional Least Squares estimators for the class (I) of bilinear models. Such estimators have a variance which is difficulty to derive analytically. The aim of the present paper is to ...