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Cira Perna

Personal Details

First Name:Cira
Middle Name:
Last Name:Perna
Suffix:
RePEc Short-ID:ppe487
[This author has chosen not to make the email address public]
http://www.unisa.it/Facolta/Economia/docenti/Perna/index.php

Affiliation

(50%) Laboratorio di Ricerca e Didattica avanzata in Statistica (STATLAB)
Dipartimento di Scienze Economiche e Statistiche (DISES)
Università degli Studi di Salerno

Fisciano, Italy
http://www.dises.unisa.it/centri_laboratori/statlab/index
RePEc:edi:stsalit (more details at EDIRC)

(50%) Dipartimento di Scienze Economiche e Statistiche (DISES)
Università degli Studi di Salerno

Fisciano, Italy
http://www.dises.unisa.it/
RePEc:edi:dssalit (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters Books

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. Michele La Rocca & Cira Perna, 2022. "Opening the Black Box: Bootstrapping Sensitivity Measures in Neural Networks for Interpretable Machine Learning," Stats, MDPI, vol. 5(2), pages 1-18, April.
  2. Maria Lucia Parrella & Giuseppina Albano & Cira Perna & Michele La Rocca, 2021. "Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets," Computational Statistics, Springer, vol. 36(4), pages 2917-2938, December.
  3. Giuseppina Albano & Francesco Giordano & Cira Perna, 2021. "On the estimation of non linear functions in stochastic volatility models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(2), pages 387-399, January.
  4. Maria Lucia Parrella & Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Reconstructing missing data sequences in multivariate time series: an application to environmental data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(2), pages 359-383, June.
  5. Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Small sample properties of ML estimator in Vasicek and CIR models: a simulation experiment," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 5-19, June.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.

Chapters

  1. Giuseppina Albano & Michele La Rocca & Cira Perna, 2021. "A Comparison Among Alternative Parameters Estimators in the Vasicek Process: A Small Sample Analysis," Springer Books, in: Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), Mathematical and Statistical Methods for Actuarial Sciences and Finance, pages 1-6, Springer.
  2. Michele Rocca & Cira Perna, 2008. "Neural Network Modelling with Applications to Euro Exchange Rates," Springer Books, in: Erricos J. Kontoghiorghes & Berç Rustem & Peter Winker (ed.), Computational Methods in Financial Engineering, pages 163-189, Springer.

Books

  1. Marco Corazza & Manfred Gilli & Cira Perna & Claudio Pizzi & Marilena Sibillo (ed.), 2021. "Mathematical and Statistical Methods for Actuarial Sciences and Finance," Springer Books, Springer, number 978-3-030-78965-7, January.
  2. Cira Perna & Marilena Sibillo (ed.), 2008. "Mathematical and Statistical Methods in Insurance and Finance," Springer Books, Springer, number 978-88-470-0704-8, January.

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

  1. Marco Corazza & Florence Legros & Cira Perna & Marilena Sibillo, 2017. "Mathematical and Statistical Methods for Actuarial Sciences and Finance," Post-Print hal-01776135, HAL.

    Cited by:

    1. Marco Corazza & Stefania Funari & Riccardo Gusso, 2012. "An evolutionary approach to preference disaggregation in a MURAME-based credit scoring problem," Working Papers 5, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    2. Marco Marozzi, 2014. "Construction, dimension reduction and uncertainty analysis of an index of trust in public institutions," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(2), pages 939-953, March.
    3. Lorenzo Mercuri & Edit Rroji, 2018. "Risk parity for Mixed Tempered Stable distributed sources of risk," Annals of Operations Research, Springer, vol. 260(1), pages 375-393, January.
    4. Gian Luca Tassinari & Michele Leonardo Bianchi, 2014. "Calibrating The Smile With Multivariate Time-Changed Brownian Motion And The Esscher Transform," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(04), pages 1-34.
    5. Boris Buchmann & Benjamin Kaehler & Ross Maller & Alexander Szimayer, 2015. "Multivariate Subordination using Generalised Gamma Convolutions with Applications to V.G. Processes and Option Pricing," Papers 1502.03901, arXiv.org, revised Oct 2016.
    6. Catalina Bolance & Montserrat Guillen & David Pitt, 2014. "Non-parametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers 2014-01, Universitat de Barcelona, UB Riskcenter.
    7. Antonella Basso & Stefania Funari, 2017. "The role of fund size in the performance of mutual funds assessed with DEA models," The European Journal of Finance, Taylor & Francis Journals, vol. 23(6), pages 457-473, May.
    8. R. Gargano & E. Otranto, 2013. "Financial Clustering in Presence of Dominant Markets," Working Paper CRENoS 201318, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    9. V. Pozdnyakov & L. M. Elbroch & C. Hu & T. Meyer & J. Yan, 2020. "On Estimation for Brownian Motion Governed by Telegraph Process with Multiple Off States," Methodology and Computing in Applied Probability, Springer, vol. 22(3), pages 1275-1291, September.
    10. Ekaterina Bulinskaya & Boris Shigida, 2021. "Discrete-Time Model of Company Capital Dynamics with Investment of a Certain Part of Surplus in a Non-Risky Asset for a Fixed Period," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 103-121, March.
    11. Luković Stevan & Marinković Srđan, 2019. "Comparative Analysis of Retirement Benefits in Private Pension Funds and Public Pension System," Economic Themes, Sciendo, vol. 57(2), pages 145-164, June.
    12. Monica Billio & Roberto Casarin & Michele Costola & Lorenzo Frattarolo, 2019. "Opinion Dynamics and Disagreements on Financial Networks," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(4), pages 24-51, December.
    13. Roman G. Smirnov & Kunpeng Wang, 2019. "The Hamiltonian approach to the problem of derivation of production functions in economic growth theory," Papers 1906.11224, arXiv.org.
    14. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    15. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    16. Michele Leonardo Bianchi & Svetlozar T. Rachev & Frank J. Fabozzi, 2018. "Calibrating the Italian Smile with Time-Varying Volatility and Heavy-Tailed Models," Computational Economics, Springer;Society for Computational Economics, vol. 51(3), pages 339-378, March.
    17. Devolder, Pierre & Melis, Roberta, 2015. "Optimal Mix Between Pay As You Go And Funding For Pension Liabilities In A Stochastic Framework," ASTIN Bulletin, Cambridge University Press, vol. 45(3), pages 551-575, September.
    18. Young Shin Kim & Rachev, Svetlozar T. & Bianchi, Michele Leonardo & Mitov, Ivan & Fabozzi, Frank J., 2010. "Time series analysis for financial market meltdowns," Working Paper Series in Economics 2, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    19. Arianna Agosto & Enrico Moretto, 2010. "Applying default probabilities in an exponential barrier structural model," Economics and Quantitative Methods qf1005, Department of Economics, University of Insubria.
    20. Vladimir Pozdnyakov & L. Mark Elbroch & Anthony Labarga & Thomas Meyer & Jun Yan, 2019. "Discretely Observed Brownian Motion Governed by Telegraph Process: Estimation," Methodology and Computing in Applied Probability, Springer, vol. 21(3), pages 907-920, September.
    21. Turcas Florin & Dumiter Florin & Brezeanu Petre & Jimon Stefania, 2016. "Theoretical and Practical Issues in Business Valuation," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 26(4), pages 1-23, November.
    22. Hasan Fallahgoul & Gregoire Loeper, 2021. "Modelling tail risk with tempered stable distributions: an overview," Annals of Operations Research, Springer, vol. 299(1), pages 1253-1280, April.
    23. Jing Shi & Marcel Ausloos & Tingting Zhu, 2017. "Benford's law first significant digit and distribution distances for testing the reliability of financial reports in developing countries," Papers 1712.00131, arXiv.org.
    24. Nikita Ratanov, 2016. "Option Pricing Under Jump-Diffusion Processes with Regime Switching," Methodology and Computing in Applied Probability, Springer, vol. 18(3), pages 829-845, September.
    25. Haruhiko Ogasawara, 2019. "The multiple Cantelli inequalities," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 495-506, September.
    26. Rick Bohte & Luca Rossini, 2019. "Comparing the Forecasting of Cryptocurrencies by Bayesian Time-Varying Volatility Models," JRFM, MDPI, vol. 12(3), pages 1-18, September.
    27. Di Bernardino Elena & Rullière Didier, 2013. "On certain transformations of Archimedean copulas: Application to the non-parametric estimation of their generators," Dependence Modeling, De Gruyter, vol. 1(2013), pages 1-36, October.
    28. Marina Resta, 2016. "VaRSOM: A Tool to Monitor Markets' Stability Based on Value at Risk and Self‐Organizing Maps," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(1-2), pages 47-64, January.
    29. Javed, Farrukh & Loperfido, Nicola & Mazur, Stepan, 2020. "Edgeworth Expansions for Multivariate Random Sums," Working Papers 2020:9, Örebro University, School of Business.
    30. Michele Leonardo Bianchi & Svetlozar T. Rachev & Frank J. Fabozzi, 2013. "Tempered stable Ornstein-Uhlenbeck processes: a practical view," Temi di discussione (Economic working papers) 912, Bank of Italy, Economic Research and International Relations Area.
    31. De Luca, Giovanni & Zuccolotto, Paola, 2013. "A Conditional Value-at-Risk Based Portfolio Selection With Dynamic Tail Dependence Clustering," MPRA Paper 50129, University Library of Munich, Germany.
    32. Gurnain Pasricha & Matteo Falagiarda & Martin Bijsterbosch & Joshua Aizenman, 2015. "Domestic and Multilateral Effects of Capital Controls in Emerging Markets," Staff Working Papers 15-37, Bank of Canada.
    33. Adam Misiorek & Rafal Weron, 2010. "Heavy-tailed distributions in VaR calculations," HSC Research Reports HSC/10/05, Hugo Steinhaus Center, Wroclaw University of Science and Technology.
    34. Fabio Baione & Davide Biancalana & Paolo Angelis, 2021. "An application of Sigmoid and Double-Sigmoid functions for dynamic policyholder behaviour," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 5-22, June.
    35. Gianna Figà-Talamanca & Marco Patacca, 2020. "Disentangling the relationship between Bitcoin and market attention measures," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(1), pages 71-91, March.
    36. Elena Di Bernardino & Didier Rullière, 2016. "On tail dependence coefficients of transformed multivariate Archimedean copulas," Post-Print hal-00992707, HAL.
    37. Urbina, Jilber & Guillén, Montserrat, 2013. "An application of capital allocation principles to operational risk," MPRA Paper 75726, University Library of Munich, Germany, revised Dec 2013.
    38. Catania, Leopoldo & Grassi, Stefano & Ravazzolo, Francesco, 2019. "Forecasting cryptocurrencies under model and parameter instability," International Journal of Forecasting, Elsevier, vol. 35(2), pages 485-501.
    39. Juchem Neto, J.P. & Claeyssen, J.C.R. & Pôrto Júnior, S.S., 2018. "Economic agglomerations and spatio-temporal cycles in a spatial growth model with capital transport cost," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 76-86.
    40. Stefania Corsaro & Valentina De Simone & Zelda Marino, 2021. "Fused Lasso approach in portfolio selection," Annals of Operations Research, Springer, vol. 299(1), pages 47-59, April.
    41. Nadine Gatzert & Katrin Osterrieder, 2020. "The future of mobility and its impact on the automobile insurance industry," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 23(1), pages 31-51, March.
    42. Martina Nardon & Paolo Pianca, 2016. "Covered call writing in a cumulative prospect theory framework," Working Papers 2016:35, Department of Economics, University of Venice "Ca' Foscari".
    43. Borak, Szymon & Misiorek, Adam & Weron, Rafal, 2010. "Models for Heavy-tailed Asset Returns," MPRA Paper 25494, University Library of Munich, Germany.
    44. Michele Leonardo Bianchi & Asmerilda Hitaj & Gian Luca Tassinari, 2020. "Multivariate non-Gaussian models for financial applications," Papers 2005.06390, arXiv.org.
    45. Marco Marozzi, 2015. "Measuring Trust in European Public Institutions," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 123(3), pages 879-895, September.
    46. Genaro Sucarrat & Alvaro Escribano, 2012. "Automated Model Selection in Finance: General-to-Specific Modelling of the Mean and Volatility Specifications," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(5), pages 716-735, October.
    47. Wojciech Charemza & Carlos Diaz Vela & Svetlana Makarova, 2013. "Too many skew normal distributions? The practitioner’s perspective," Discussion Papers in Economics 13/07, Division of Economics, School of Business, University of Leicester.
    48. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    49. Elisa Pagani, 2015. "Certainty Equivalent: Many Meanings of a Mean," Working Papers 24/2015, University of Verona, Department of Economics.
    50. Svetlozar Rachev & Frank J. Fabozzi & Boryana Racheva-Iotova & Abootaleb Shirvani, 2017. "Option Pricing with Greed and Fear Factor: The Rational Finance Approach," Papers 1709.08134, arXiv.org, revised Mar 2020.
    51. Paola Ferretti & Antonella Campana, 2011. "XL reinsurance with reinstatements and initial premium feasibility in exchangeability hypothesis," Working Papers 2011_14, Department of Economics, University of Venice "Ca' Foscari".
    52. Nikita Ratanov, 2021. "Ornstein-Uhlenbeck Processes of Bounded Variation," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 925-946, September.
    53. Michele Leonardo Bianchi, 2014. "Are the log-returns of Italian open-end mutual funds normally distributed? A risk assessment perspective," Temi di discussione (Economic working papers) 957, Bank of Italy, Economic Research and International Relations Area.
    54. Michele Bianchi & Frank Fabozzi, 2014. "Discussion of ‘on simulation and properties of the stable law’ by Devroye and James," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(3), pages 353-357, August.
    55. Elena Di Bernardino & Didier Rullière, 2015. "Estimation of multivariate critical layers: Applications to rainfall data," Post-Print hal-00940089, HAL.
    56. Maria Iannario, 2012. "Modelling shelter choices in a class of mixture models for ordinal responses," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(1), pages 1-22, March.
    57. Antonio Di Crescenzo & Shelemyahu Zacks, 2015. "Probability Law and Flow Function of Brownian Motion Driven by a Generalized Telegraph Process," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 761-780, September.
    58. Flavia Barsotti & Simona Sanfelici, 2016. "Market Microstructure Effects on Firm Default Risk Evaluation," Econometrics, MDPI, vol. 4(3), pages 1-31, July.
    59. Giovanni De Luca & Paola Zuccolotto, 2017. "Dynamic tail dependence clustering of financial time series," Statistical Papers, Springer, vol. 58(3), pages 641-657, September.
    60. Claudio Fontana & Juan Miguel A. Montes, 2012. "A unified approach to pricing and risk management of equity and credit risk," Papers 1212.5395, arXiv.org, revised May 2013.
    61. Luca GRILLI & Massimo Alfonso RUSSO & Roberto GISMONDI, 2012. "Methodological Proposals For A Qualitative Evaluation Of Italian Durum Wheat Varieties," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 7(2(20)/ Su), pages 103-122.
    62. Martina Nardon & Paolo Pianca, 2014. "European option pricing with constant relative sensitivity probability weighting function," Working Papers 2014:25, Department of Economics, University of Venice "Ca' Foscari".
    63. Martina Nardon & Paolo Pianca, 2019. "European option pricing under cumulative prospect theory with constant relative sensitivity probability weighting functions," Computational Management Science, Springer, vol. 16(1), pages 249-274, February.
    64. Vincenzo Candila, 2021. "Multivariate Analysis of Cryptocurrencies," Econometrics, MDPI, vol. 9(3), pages 1-17, July.
    65. Stefania Capecchi & Maria Iannario & Rosaria Simone, 2018. "Well-Being and Relational Goods: A Model-Based Approach to Detect Significant Relationships," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 729-750, January.
    66. Francesco Battaglia & Domenico Cucina & Manuel Rizzo, 2020. "Detection and estimation of additive outliers in seasonal time series," Computational Statistics, Springer, vol. 35(3), pages 1393-1409, September.
    67. Alonso González, Pablo J., 2017. "Estimating life expectancy free of dependency : group characterization through the proximity to the deepest dependency path," DES - Working Papers. Statistics and Econometrics. WS 24672, Universidad Carlos III de Madrid. Departamento de Estadística.
    68. Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Small sample properties of ML estimator in Vasicek and CIR models: a simulation experiment," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 5-19, June.
    69. Roman G. Smirnov & Kunpeng Wang, 2017. "In search of a new economic model determined by logistic growth," Papers 1711.02625, arXiv.org, revised Oct 2018.

Articles

  1. Maria Lucia Parrella & Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Reconstructing missing data sequences in multivariate time series: an application to environmental data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(2), pages 359-383, June.

    Cited by:

    1. Maria Lucia Parrella & Giuseppina Albano & Cira Perna & Michele La Rocca, 2021. "Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets," Computational Statistics, Springer, vol. 36(4), pages 2917-2938, December.
    2. Yohan Kim & Scott Kelly & Deepu Krishnan & Jay Falletta & Kerryn Wilmot, 2022. "Strategies for Imputation of High-Resolution Environmental Data in Clinical Randomized Controlled Trials," IJERPH, MDPI, vol. 19(3), pages 1-17, January.

  2. Giuseppina Albano & Michele La Rocca & Cira Perna, 2019. "Small sample properties of ML estimator in Vasicek and CIR models: a simulation experiment," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 42(1), pages 5-19, June.

    Cited by:

    1. Albano, G. & Giorno, V., 2020. "Inferring time non-homogeneous Ornstein Uhlenbeck type stochastic process," Computational Statistics & Data Analysis, Elsevier, vol. 150(C).

  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.

    Cited by:

    1. Ivan Letteri & Giuseppe Della Penna & Giovanni De Gasperis & Abeer Dyoub, 2022. "A Stock Trading System for a Medium Volatile Asset using Multi Layer Perceptron," Papers 2201.12286, arXiv.org.
    2. 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.
    3. 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.
    4. 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.
    5. Xie, Yuying & Li, Chaoshun & Tang, Geng & Liu, Fangjie, 2021. "A novel deep interval prediction model with adaptive interval construction strategy and automatic hyperparameter tuning for wind speed forecasting," Energy, Elsevier, vol. 216(C).
    6. 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.
    7. Artemisa Zaragoza-Ibarra & Gerardo G. Alfaro-Calderón & Víctor G. Alfaro-García & Fernando Ornelas-Tellez & Rodrigo Gómez-Monge, 2021. "A machine learning model of national competitiveness with regional statistics of public expenditure," Computational and Mathematical Organization Theory, Springer, vol. 27(4), pages 451-468, December.
    8. Tsao, Hao-Han & Leu, Yih-Guang & Chou, Li-Fen, 2021. "A center-of-concentrated-based prediction interval for wind power forecasting," Energy, Elsevier, vol. 237(C).
    9. 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.
    10. Dimitris N. Politis & Kejin Wu, 2023. "Multi-Step-Ahead Prediction Intervals for Nonparametric Autoregressions via Bootstrap: Consistency, Debiasing, and Pertinence," Stats, MDPI, vol. 6(3), pages 1-29, August.

  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.

    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. Michele La Rocca & Cira Perna, 2022. "Opening the Black Box: Bootstrapping Sensitivity Measures in Neural Networks for Interpretable Machine Learning," Stats, MDPI, vol. 5(2), pages 1-18, April.
    5. 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.
    6. Steven M. Ramsey & Jason S. Bergtold, 2021. "Examining Inferences from Neural Network Estimators of Binary Choice Processes: Marginal Effects, and Willingness-to-Pay," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1137-1165, December.
    7. 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.

Chapters

    Sorry, no citations of chapters recorded.

Books

  1. Cira Perna & Marilena Sibillo (ed.), 2008. "Mathematical and Statistical Methods in Insurance and Finance," Springer Books, Springer, number 978-88-470-0704-8, January.

    Cited by:

    1. Magdalena Homa, 2022. "The Impact of MT Strategies on Risk and Value Distribution of Unit-linked Insurance Portfolio," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 607-619.
    2. Luca GRILLI & Massimo Alfonso RUSSO & Roberto GISMONDI, 2012. "Methodological Proposals For A Qualitative Evaluation Of Italian Durum Wheat Varieties," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 7(2(20)/ Su), pages 103-122.
    3. Varsha S. Kulkarni, 2013. "Complexity, Chaos, and the Duffing-Oscillator Model: An Analysis of Inventory Fluctuations in Markets," Papers 1308.1616, arXiv.org.
    4. Jochen Papenbrock & Peter Schwendner, 2015. "Handling risk-on/risk-off dynamics with correlation regimes and correlation networks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 29(2), pages 125-147, May.

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