My bibliography
Save this item
From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Paolo Giordani, 2015. "Lasso-constrained regression analysis for interval-valued data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(1), pages 5-19, March.
- Lin, Wei & González-Rivera, Gloria, 2016.
"Interval-valued time series models: Estimation based on order statistics exploring the Agriculture Marketing Service data,"
Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 694-711.
- Gloria Gonzalez-Rivera & Wei Lin, 2015. "Interval-valued Time Series Models: Estimation based on Order Statistics. Exploring the Agriculture Marketing Service Data," Working Papers 201505, University of California at Riverside, Department of Economics.
- J. Le-Rademacher & L. Billard, 2013. "Principal component histograms from interval-valued observations," Computational Statistics, Springer, vol. 28(5), pages 2117-2138, October.
- Miguel de Carvalho & Gabriel Martos, 2022. "Modeling interval trendlines: Symbolic singular spectrum analysis for interval time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 167-180, January.
- Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ougouyandjou, 2020. "On Random Extended Intervals and their ARMA Processes," Working Papers hal-03169516, HAL.
- van Dijk, Bram & Paap, Richard, 2008.
"Explaining individual response using aggregated data,"
Journal of Econometrics, Elsevier, vol. 146(1), pages 1-9, September.
- Paap, R. & van Dijk, A., 2006. "Explaining individual response using aggregated data," Econometric Institute Research Papers EI 2006-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Paola Zuccolotto, 2012. "Principal component analysis with interval imputed missing values," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 1-23, January.
- Rong Guan & Huiwen Wang & Haitao Zheng, 2020. "Improving accuracy of financial distress prediction by considering volatility: an interval-data-based discriminant model," Computational Statistics, Springer, vol. 35(2), pages 491-514, June.
- Liang-Ching Lin & Li-Hsien Sun, 2019. "Modeling financial interval time series," PLOS ONE, Public Library of Science, vol. 14(2), pages 1-20, February.
- Qing Liu & Huina Jin & Xiang Bai & Jinliang Zhang, 2023. "Prediction and Analysis of the Price of Carbon Emission Rights in Shanghai: Under the Background of COVID-19 and the Russia–Ukraine Conflict," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
- António Silva & Paula Brito, 2006. "Linear discriminant analysis for interval data," Computational Statistics, Springer, vol. 21(2), pages 289-308, June.
- Gloria Gonzalez-Rivera & Javier Arroyo & Carlos Mate & A. Munoz San Roque, 2011. "Smoothing Methods for Histogram-valued Time Series. An Application to Value-at-Risk," Working Papers 201433, University of California at Riverside, Department of Economics.
- Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt’s exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759.
- Eufr�sio de A. Lima Neto & Ulisses U. dos Anjos, 2015. "Regression model for interval-valued variables based on copulas," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(9), pages 2010-2029, September.
- Carlo Drago, 2021.
"The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach,"
Economies, MDPI, vol. 9(4), pages 1-17, October.
- Drago, Carlo, 2020. "The Analysis and the Measurement of Poverty: An Interval Based Composite Indicator Approach," MPRA Paper 104462, University Library of Munich, Germany.
- Drago, Carlo, 2021. "The Analysis and the Measurement of Poverty: An Interval-Based Composite Indicator Approach," MPRA Paper 109307, University Library of Munich, Germany.
- J. Le-Rademacher & L. Billard, 2017. "Principal component analysis for histogram-valued data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 327-351, June.
- Meiling Chen & Huiwen Wang & Zhongfeng Qin, 2015. "Principal component analysis for probabilistic symbolic data: a more generic and accurate algorithm," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(1), pages 59-79, March.
- A. Silva & Paula Brito, 2015. "Discriminant Analysis of Interval Data: An Assessment of Parametric and Distance-Based Approaches," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 516-541, October.
- Sun, Yuying & Han, Ai & Hong, Yongmiao & Wang, Shouyang, 2018. "Threshold autoregressive models for interval-valued time series data," Journal of Econometrics, Elsevier, vol. 206(2), pages 414-446.
- Antonio Calcagnì & Luigi Lombardi & Lorenzo Avanzi & Eduardo Pascali, 2020. "Multiple mediation analysis for interval-valued data," Statistical Papers, Springer, vol. 61(1), pages 347-369, February.
- Lima Neto, Eufrásio de A. & de Carvalho, Francisco de A.T., 2010. "Constrained linear regression models for symbolic interval-valued variables," Computational Statistics & Data Analysis, Elsevier, vol. 54(2), pages 333-347, February.
- Sun, Yuying & Bao, Qin & Zheng, Jiali & Wang, Shouyang, 2020. "Assessing the price dynamics of onshore and offshore RMB markets: An ITS model approach," China Economic Review, Elsevier, vol. 62(C).
- Angela Blanco-Fernández & Peter Winker, 2016. "Data generation processes and statistical management of interval data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(4), pages 475-494, October.
- Lingjun Wang & Ying Wang & Jian Chen, 2019. "Assessment of the Ecological Niche of Photovoltaic Agriculture in China," Sustainability, MDPI, vol. 11(8), pages 1-17, April.
- Yan Sun & Guanghua Lian & Zudi Lu & Jennifer Loveland & Isaac Blackhurst, 2020. "Modeling the Variance of Return Intervals Toward Volatility Prediction," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 492-519, July.
- Paula Brito & A. Pedro Duarte Silva, 2012. "Modelling interval data with Normal and Skew-Normal distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(1), pages 3-20, March.
- Gil, Maria Angeles & Gonzalez-Rodriguez, Gil & Colubi, Ana & Montenegro, Manuel, 2007. "Testing linear independence in linear models with interval-valued data," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 3002-3015, March.
- Hao, Peng & Guo, Junpeng, 2017. "Constrained center and range joint model for interval-valued symbolic data regression," Computational Statistics & Data Analysis, Elsevier, vol. 116(C), pages 106-138.
- Sun, Yuying & Zhang, Xinyu & Wan, Alan T.K. & Wang, Shouyang, 2022. "Model averaging for interval-valued data," European Journal of Operational Research, Elsevier, vol. 301(2), pages 772-784.
- Philip Hans Franses & Max Welz, 2022.
"Evaluating heterogeneous forecasts for vintages of macroeconomic variables,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(4), pages 829-839, July.
- Franses, Ph.H.B.F. & Welz, M., 2018. "Evaluating heterogeneous forecasts for vintages of macroeconomic variables," Econometric Institute Research Papers EI2018-47, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Gatto, Andrea & Drago, Carlo & Panarello, Demetrio & Aldieri, Luigi, 2023. "Energy transition in China: Assessing progress in sustainable development and resilience directions," International Economics, Elsevier, vol. 176(C).
- Yan Sun & Dan Ralescu, 2015. "A normal hierarchical model and minimum contrast estimation for random intervals," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 67(2), pages 313-333, April.
- Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
- Drago, Carlo, 2015.
"Exploring the Community Structure of Complex Networks,"
MPRA Paper
81024, University Library of Munich, Germany.
- Drago, Carlo, 2016. "Exploring the Community Structure of Complex Networks," ETA: Economic Theory and Applications 244529, Fondazione Eni Enrico Mattei (FEEM).
- Carlo Drago, 2016. "Exploring the Community Structure of Complex Networks," Working Papers 2016.57, Fondazione Eni Enrico Mattei.
- Samadi, S. Yaser & Billard, Lynne, 2021. "Analysis of dependent data aggregated into intervals," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
- Wei Yang & Ai Han & Yongmiao Hong & Shouyang Wang, 2016. "Analysis of crisis impact on crude oil prices: a new approach with interval time series modelling," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1917-1928, December.
- Dias, Sónia & Brito, Paula & Amaral, Paula, 2021. "Discriminant analysis of distributional data via fractional programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 206-218.
- Fei Liu & L. Billard, 2022. "Partition of Interval-Valued Observations Using Regression," Journal of Classification, Springer;The Classification Society, vol. 39(1), pages 55-77, March.
- Gloria Gonzalez-Rivera & Wei Lin, 2014. "Interval-valued Time Series: Model Estimation based on Order Statistics," Working Papers 201429, University of California at Riverside, Department of Economics.
- M. Rosário Oliveira & Margarida Azeitona & António Pacheco & Rui Valadas, 2022. "Association measures for interval variables," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(3), pages 491-520, September.
- Drago, Carlo, 2021. "Interval-Based Composite Indicators with a Triplex Representation: A Measure of the Potential Demand for the "Ristori" Decree in Italy," MPRA Paper 106904, University Library of Munich, Germany.
- Antonio Balzanella & Antonio Irpino, 2020. "Spatial prediction and spatial dependence monitoring on georeferenced data streams," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 101-128, March.
- Guo, Junpeng & Li, Wenhua & Li, Chenhua & Gao, Sa, 2012. "Standardization of interval symbolic data based on the empirical descriptive statistics," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 602-610.
- Carlo Drago & Roberto Ricciuti, 2019.
"An interval variables approach to address measurement uncertainty in governance indicators,"
Economics Bulletin, AccessEcon, vol. 39(1), pages 626-635.
- Carlo Drago & Roberto Ricciuti, 2018. "An Interval Variables Approach to Address Measurement Uncertainty in Governance Indicators," Working Papers 02/2018, University of Verona, Department of Economics.
- Babel Raïssa Guemdjo Kamdem & Jules Sadefo Kamdem & Carlos Ogouyandjou, 2024. "An abelian way approach to study random extended intervals and their ARMA processes," Post-Print hal-04506343, HAL.
- Babel Raïssa Guemdjo Kamdem & Jules Sadefo-Kamdem & Carlos Ogouyandjou, 2021. "An Abelian Group way to study Random Extended Intervals and their ARMA Processes," Working Papers hal-03174631, HAL.
- Gloria Gonzalez-Rivera & Javier Arroyo & Carlos Mate, 2011. "Forecasting with Interval and Histogram Data. Some Financial Applications," Working Papers 201438, University of California at Riverside, Department of Economics.
- Drago, Carlo, 2015.
"Exploring the Community Structure of Complex Networks,"
MPRA Paper
81024, University Library of Munich, Germany.
- Drago, Carlo, 2016. "Exploring the Community Structure of Complex Networks," ET: Economic Theory 244529, Fondazione Eni Enrico Mattei (FEEM).
- Carlo Drago, 2016. "Exploring the Community Structure of Complex Networks," Working Papers 2016.57, Fondazione Eni Enrico Mattei.
- Liang-Ching Lin & Hsiang-Lin Chien & Sangyeol Lee, 2021. "Symbolic interval-valued data analysis for time series based on auto-interval-regressive models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 295-315, March.
- Ana Belén Ramos-Guajardo, 2022. "A hierarchical clustering method for random intervals based on a similarity measure," Computational Statistics, Springer, vol. 37(1), pages 229-261, March.
- Qing Zhao & Huiwen Wang & Shanshan Wang, 2023. "Robust regression for interval-valued data based on midpoints and log-ranges," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 583-621, September.
- Karel Hron & Paula Brito & Peter Filzmoser, 2017. "Exploratory data analysis for interval compositional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 223-241, June.
- A. Pedro Duarte Silva & Peter Filzmoser & Paula Brito, 2018. "Outlier detection in interval data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 785-822, September.
- Sri Winarni & Sapto Wahyu Indratno & Restu Arisanti & Resa Septiani Pontoh, 2024. "Image Feature Extraction Using Symbolic Data of Cumulative Distribution Functions," Mathematics, MDPI, vol. 12(13), pages 1-17, July.
- García-Ascanio, Carolina & Maté, Carlos, 2010. "Electric power demand forecasting using interval time series: A comparison between VAR and iMLP," Energy Policy, Elsevier, vol. 38(2), pages 715-725, February.
- Massimo Aria & Antonio D’Ambrosio & Carmela Iorio & Roberta Siciliano & Valentina Cozza, 2020. "Dynamic recursive tree-based partitioning for malignant melanoma identification in skin lesion dermoscopic images," Statistical Papers, Springer, vol. 61(4), pages 1645-1661, August.
- Boris Beranger & Huan Lin & Scott Sisson, 2023. "New models for symbolic data analysis," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 659-699, September.
- Christiane Guinot & Denis Malvy & Jean-François Schémann & Filipe Afonso & Raja Haddad & Edwin Diday, 2015. "Strategies evaluation in environmental conditions by symbolic data analysis: application in medicine and epidemiology to trachoma," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(1), pages 107-119, March.
- Lima Neto, Eufrasio de A. & de Carvalho, Francisco de A.T., 2008. "Centre and Range method for fitting a linear regression model to symbolic interval data," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1500-1515, January.
- Buzzigoli, Lucia & Giusti, Antonio, 2006. "From Marginals to Array Structure with the Shuttle Algorithm," MPRA Paper 49245, University Library of Munich, Germany.
- Paulo M.M. Rodrigues & Nazarii Salish, 2011. "Modeling and Forecasting Interval Time Series with Threshold Models: An Application to S&P500 Index Returns," Working Papers w201128, Banco de Portugal, Economics and Research Department.
- Antonio Irpino & Rosanna Verde, 2015. "Basic statistics for distributional symbolic variables: a new metric-based approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 9(2), pages 143-175, June.
- Cheolwoo Park & Yongho Jeon & Kee-Hoon Kang, 2016. "An exploratory data analysis in scale-space for interval-valued data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(14), pages 2643-2660, October.
- Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt's exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759, July.
- Nataša Kejžar & Simona Korenjak-Černe & Vladimir Batagelj, 2021. "Clustering of modal-valued symbolic data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(2), pages 513-541, June.
- Arroyo, Javier & Maté, Carlos, 2009. "Forecasting histogram time series with k-nearest neighbours methods," International Journal of Forecasting, Elsevier, vol. 25(1), pages 192-207.
- Chang, Meng-Shiuh & Ju, Peijie & Liu, Yilei & Hsueh, Shao-Chieh, 2022. "Determining hedges and safe havens for stocks using interval analysis," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).