Francesco Giordano

发表

Multiple Testing for Different Structures of Spatial Dynamic Panel Data Models

Massimo Pacella, Francesco Giordano, Maria Lucia Parrella, 2018 .

Standard error estimation in neural network regression models: the moving block bootstrap approach

Francesco Giordano, Michele La Rocca, Cira Perna, 2001 .

Nonparametric estimation of the dynamic range of music signals

Francesco Giordano, Pietro Coretto, 2017 .

Neural Networks for Bandwidth Selection in Non-Parametric Derivative Estimation

Francesco Giordano, Maria Lucia Parrella, 2008 .

Detecting Short-Term Cycles in Complex Time Series Databases

Francesco Giordano, Maria Lucia Parrella, Marialuisa Restaino, 2012 .

Nonparametric estimation of volatility functions: Some experimental evidences

Francesco Giordano, Michele La Rocca, Cira Perna, 2012 .

A locally adaptive bandwidth selector for kernel based regression

Francesco Giordano, Maria Lucia Parrella, 2009 .

A fast subsampling method for estimating the distribution of signal-to-noise ratio statistics in nonparametric time series regression models

Francesco Giordano, Pietro Coretto, Pietro Coretto, 2017 .

Neural Network Sieve Bootstrap Prediction Intervals: Some Real Data Evidence

Francesco Giordano, Michele La Rocca, Cira Perna, 2009, WIRN.

Bootstrap prediction intervals with neural networks in nonlinear time series

Francesco Giordano, Michele La Rocca, Cira Perna, 2003 .

Bootstrap Variables Selection in Neural Network Regression Models

Francesco Giordano, Michele La Rocca, Cira Perna, 2004 .

Homothetic Triangle Contact Representations of Planar Graphs

Stefan Felsner, Emilio Di Giacomo, Walter Didimo, 2007, CCCG.

Computing upward topological book embeddings of upward planar digraphs

Antonios Symvonis, Giuseppe Liotta, Francesco Giordano, 2007, J. Discrete Algorithms.

Value-at-Risk Inference with NN-Sieve Bootstrap

Francesco Giordano, Michele La Rocca, Cira Perna, 2011 .

Upward Topological Book Embeddings of DAGs

Emilio Di Giacomo, Giuseppe Liotta, Francesco Giordano, 2011, SIAM J. Discret. Math..

Estimating the Conditional Mean of a Non-linear Time Series Using Neural Networks

Francesco Giordano, Cira Perna, 1999 .

Bias-corrected inference for multivariate nonparametric regression: Model selection and oracle property

Francesco Giordano, Maria Lucia Parrella, F. Giordano, 2016, J. Multivar. Anal..

On the RODEO Method for Variable Selection

Francesco Giordano, Maria Lucia Parrella, 2014 .

TESTING DIFFERENT STRUCTURES OF SPATIAL DYNAMIC PANEL DATA MODELS

Massimo Pacella, Francesco Giordano, Maria Lucia Parrella, 2017 .

Detecting cycles in Complex Time Series Databases

Francesco Giordano, Maria Lucia Parrella, Marialuisa Restaino, 2008 .

Neural Networks and Bootstrap Methods for Regression Models with Dependent Errors

Francesco Giordano, Michele La Rocca, Cira Perna, 2009 .

Integrating Sensors into a Marine Drone for Bathymetric 3D Surveys in Shallow Waters

Francesco Giordano, Francesco Peluso, Claudio Parente, 2015, Sensors.

Vehicle-to-Home Usage Scenarios for Self-Consumption Improvement of a Residential Prosumer With Photovoltaic Roof

Francesco Giordano, Alberto Tenconi, Silvio Vaschetto, 2020, IEEE Transactions on Industry Applications.

Clustering Complex Time Series Databases

Francesco Giordano, Maria Lucia Parrella, Michele La Rocca, 2011 .

Maximum upward planar subgraphs of embedded planar digraphs

Walter Didimo, Francesco Giordano, Carla Binucci, 2007, Comput. Geom..

STRUCTURE DISCOVERING IN NONPARAMETRIC REGRESSION BY THE GRID PROCEDURE

Francesco Giordano, Maria Lucia Parrella, Soumendra N. Lahiri, 2019 .

The hidden layer size in feed-forward neural networks: a statistical point of view.

Francesco Giordano, Cira Perna, 1999 .

A comment on “An analysis of global warming in the Alpine Region based on nonlinear nonstationary time series models” by F. Battaglia and M. K. Protopapas

Francesco Giordano, Cira Perna, Cosimo Vitale, 2012, Stat. Methods Appl..

Periodical feature based time series clustering

Francesco Giordano, Maria Lucia Parrella, Michele La Rocca, 2015 .

Forecasting nonlinear time series with neural network sieve bootstrap

Francesco Giordano, Michele La Rocca, Cira Perna, 2007, Comput. Stat. Data Anal..

Parametric and Non-Parametric Methods in Non-linear Time Series Analysis: a Critical evaluation

Francesco Giordano, Cira Perna, Alessandra Amendola, 1998 .

A Monte Carlo subsampling method for estimating the distribution of signal-to-noise ratio statistics in nonparametric time series regression models

Francesco Giordano, Pietro Coretto, 2020 .

Upward Spirality and Upward Planarity Testing

Walter Didimo, Giuseppe Liotta, Francesco Giordano, 2005, SIAM J. Discret. Math..

Upward Spirality and Upward Planarity Testing

Walter Didimo, Giuseppe Liotta, Francesco Giordano, 2005, Graph Drawing.

Embeddability Problems for Upward Planar Digraphs

Giuseppe Liotta, Francesco Giordano, Sue Whitesides, 2009, GD.

Neural networks for bandwidth selection in local linear regression of time series

Francesco Giordano, Maria Lucia Parrella, F. Giordano, 2008, Comput. Stat. Data Anal..

Standard Error Estimation in Neural Network Regression Models: the AR-Sieve Bootstrap Approach

Francesco Giordano, Michele La Rocca, Cira Perna, 2001, WIRN.

Clustering complex time-series databases by using periodic components

Francesco Giordano, Maria Lucia Parrella, Michele La Rocca, 2017, Stat. Anal. Data Min..

A new procedure for variable selection in presence of rare events

Francesco Giordano, Marcella Niglio, Marialuisa Restaino, 2020, J. Oper. Res. Soc..

Overlapping cluster planarity

Walter Didimo, Giuseppe Liotta, Francesco Giordano, 2007, 2007 6th International Asia-Pacific Symposium on Visualization.

MICROVEGA (MICRO VESSEL FOR GEODETICS APPLICATION): A MARINE DRONE FOR THE ACQUISITION OF BATHYMETRIC DATA FOR GIS APPLICATIONS

Francesco Giordano, Francesco Peluso, Gaia Mattei, 2015 .

Maximum Upward Planar Subgraphs of Embedded Planar Digraphs

Walter Didimo, Francesco Giordano, Carla Binucci, 2007, Graph Drawing.

Clustering nonlinear time series with neural network bootstrap forecast distributions

Francesco Giordano, Michele La Rocca, Cira Perna, 2021, Int. J. Approx. Reason..

Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction

Francesco Giordano, Maria Lucia Parrella, Marialuisa Restaino, 2017, Applied Stochastic Models in Business and Industry.

Input Variable Selection in Neural Network Models

Francesco Giordano, Michele La Rocca, Cira Perna, 2014 .