IDEAS home Printed from https://ideas.repec.org/f/ppe487.html
   My authors  Follow this author

Cira Perna

Personal Details

First Name:Cira
Middle Name:
Last Name:Perna
Suffix:
RePEc Short-ID:ppe487
http://www.unisa.it/Facolta/Economia/docenti/Perna/index.php

Affiliation

(in no particular order)

Dipartimento di Scienze Economiche e Statistiche (DISES) (Department of Economics and Statistics)
Università degli Studi di Salerno (University of Salerno)

Fisciano, Italy
http://www.dises.unisa.it/

089-963132
089-962049
Via Ponte Don Melillo - 84084 Fisciano (SA)
RePEc:edi:dssalit (more details at EDIRC)

Laboratorio di Ricerca e Didattica avanzata in Statistica (STATLAB) (Laboratory for Research and Advanced Training)
Dipartimento di Scienze Economiche e Statistiche (DISES) (Department of Economics and Statistics)
Università degli Studi di Salerno (University of Salerno)

Fisciano, Italy
http://www.dises.unisa.it/centri_laboratori/statlab/index

+39 089 963132
+39 089 962049
Via Ponte Don Melillo - 84084 Fisciano (SA)
RePEc:edi:stsalit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Marco Corazza & Florence Legros & Cira Perna & Marilena Sibillo, 2017. "Mathematical and Statistical Methods for Actuarial Sciences and Finance," Post-Print hal-01776135, HAL.
  2. Michele La Rocca & Cira Perna, 2006. "A multiple testing procedure for neural network model selection," Computing in Economics and Finance 2006 497, Society for Computational Economics.
  3. Michele La Rocca & Francesco Giordano & Cira Perna, 2000. "Inference Based On Resampling Techniques For Neural Networks In Regression Models," Computing in Economics and Finance 2000 52, Society for Computational Economics.

Articles

  1. Francesco Giordano & Cira Perna & Cosimo Vitale, 2012. "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," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 355-361, August.
  2. F. Giordano & M. La Rocca & C. Perna, 2011. "Properties of the neural network sieve bootstrap," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(3), pages 803-817.
  3. Giordano, Francesco & La Rocca, Michele & Perna, Cira, 2007. "Forecasting nonlinear time series with neural network sieve bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3871-3884, May.
  4. La Rocca, Michele & Perna, Cira, 2005. "Variable selection in neural network regression models with dependent data: a subsampling approach," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 415-429, February.
  5. Cira Perna & Francesco Giordano, 2001. "The hidden layer size in feed-forward neural networks: a statistical point of view," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 217-227.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

    Sorry, no citations of working papers recorded.

Articles

  1. Giordano, Francesco & La Rocca, Michele & Perna, Cira, 2007. "Forecasting nonlinear time series with neural network sieve bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3871-3884, May.

    Cited by:

    1. Alonso, Andres M. & Sipols, Ana E., 2008. "A time series bootstrap procedure for interpolation intervals," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1792-1805, January.
    2. Vilar, J.A. & Alonso, A.M. & Vilar, J.M., 2010. "Non-linear time series clustering based on non-parametric forecast densities," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2850-2865, November.
    3. Fuertes, Ana-Maria, 2008. "Sieve bootstrap t-tests on long-run average parameters," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3354-3370, March.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
    5. Catalina Lucia COCIANU & Hakob GRIGORYAN, 2015. "An Artificial Neural Network for Data Forecasting Purposes," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 19(2), pages 34-45.

  2. La Rocca, Michele & Perna, Cira, 2005. "Variable selection in neural network regression models with dependent data: a subsampling approach," Computational Statistics & Data Analysis, Elsevier, vol. 48(2), pages 415-429, February.

    Cited by:

    1. Giordano, Francesco & Parrella, Maria Lucia, 2016. "Bias-corrected inference for multivariate nonparametric regression: Model selection and oracle property," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 71-93.
    2. Francesco Giordano & Maria Lucia Parrella, 2014. "Bias-corrected inference for multivariate nonparametric regression: model selection and oracle property," Working Papers 3_232, Dipartimento di Scienze Economiche e Statistiche, Università degli Studi di Salerno.
    3. Dalibor Petković & Milan Gocic & Slavisa Trajkovic & Miloš Milovančević & Dragoljub Šević, 2017. "Precipitation concentration index management by adaptive neuro-fuzzy methodology," Climatic Change, Springer, vol. 141(4), pages 655-669, April.
    4. Giordano, Francesco & La Rocca, Michele & Perna, Cira, 2007. "Forecasting nonlinear time series with neural network sieve bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3871-3884, May.
    5. Wu, Edmond H.C. & Yu, Philip L.H. & Li, W.K., 2009. "A smoothed bootstrap test for independence based on mutual information," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2524-2536, May.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Cira Perna should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.