Orietta Nicolis

Doctor en Estadística aplicada a las Ciencias Económicas y Sociales. Universitá degli Studi di Padova Italia. 1999.

Cargo: Profesora Investigadora

Líneas de Investigación e intereses:

  • Estadística metodológica y aplicada
  • Análisis de series de tiempo
  • Estadística espacial y geoestadística
  • Modelos espacio-temporales y aplicaciones
  • Procesos de puntos y aplicaciones
  • Análisis wavelets y de la fractalidad
  • Machine learning y redes neuronales

Contacto: orietta.nicolis@unab.cl

  • Marcelo Alejandro Rodríguez Gallardo. Small area estimation based on Birnbaum-Saunders models. Doctor en Estadística, Universidad de Valparaíso, 2017.
  • Luis Mario Riquelme Quezada. Proceso de Cox Temporal con Proceso de Intensidad Folded-Normal. Doctor en Estadística, Universidad de Valparaíso, 2018.
  • Joaquin Cavieres Gaete. Methodology to predict nominal fishing effort of the hedgehog (Loxechinus albus) in the X and XI Region using a geostatistical spatio – temporal model. Magíster en Estadística, Universidad de Valparaíso, 2016.
  • Eduardo Puraivan H. Geostatistical analysis of air pollution data in Santiago, Chile, using SPDE with INLA estimation method. Magister en Estadística, Universidad de Valparaíso, 2016.
  • Lina Marcela Aristizbal Soto. Spatio-temporal interpolation for the estimation of missing values in PM2.5 data and their impact on health. Magister en Estadística, Universidad de Valparaíso, 2015.
  • Camilo Lillo. Extreme Value Birnbaum-Saunders distribution: regression models and Lmoments. Magister en Estadística, Universidad de Valparaíso, 2015.
  • Dario Plebani. La reducción de la escala de los datos de precipitación en el norte de Italia a través de un modelo de “downscaling” de precipitación. Magister en Ingeniería, Universidad degli studi di Bergamo (Italia), 2011.
  • Davide Calegari. Definición de una metodología para evaluar el desempeño ambiental de los sistemas de aislamiento. Magister en Ingeniería, Universidad degli studi di Bergamo (Italia), 2009.
  • Lorenzo Piccirillo. El análisis de la precipitación en la región de Lombardía y el diseño de sistemas de drenaje. Magister en Ingeniería, Universidad degli studi di Bergamo (Italia), 2008.
  • Luca Gherardi y Carlo Piantoni. Caracterización de campos, análisis estadístico y herramientas de clasificación para el monitoreo geodésico. Magister en Ingeniería, Universidad degli studi di Bergamo (Italia), 2006.
  • Josè Antonio Arenas Valencia. Modelo de redes neuronales para la predicción de la calidad del aire (O3) en la Región Metropolitana de Santiago. Ingeniero Estadístico, Universidad de Valparaíso, 2017.
  • Jesus Ibacache. Modelo para series temporales cíclicas estimado bajo el dominio del tiempo y frecuencia con aplicación en contaminante ozono. Ingeniero Estadístico, Universidad de Valparaíso, 2016.
  • Marcela Paz Azcar Pizarro. Diseño de modelo de pronóstico de la calidad del aire (PM2,5) en la Región Metropolitana. Ingeniero Estadístico, Universidad de Valparaíso, 2015.
  • Daniela Francisca Hellman Rodriguez. Método estadístico para la evaluación del
    riesgo sísmico. Ingeniero Estadístico, Universidad de Valparaíso, 2014.
  • Cristobal Eduardo Roco Saavedra. Aplicación de técnicas geoestadisticas y de diagnostico para el análisis de la calidad del aire en la ciudad de Santiago. Ingeniero Estadístico, Universidad de Valparaíso, 2014.

Libros

  • Nicolis, O., Tondini, G. (2000). Modellizzazione e previsione delle serie storiche con tecniche non lineari, un nuovo approccio combinando reti neurali ed analisi dello spettro singolare, Libreria Universitaria Editrice, Verona.

Capítulos de libros

  • Nicolis, O. Díaz, M.,Cuevas, O. (2018) A spatio-temporal approach for predicting wind speed along the coast of Valparaiso, Chile. In: M. Cameletti and F. Finazzi (Eds) Quantitative Methods in Environmental and Climate Research. Springer.
  • Nicolis, O., Chiodi, M, Adelfio, G. (2017). Space-Time Forecasting of Seismic Events in Chile. In Earthquakes – Tectonics, Hazard and Risk Mitigation, (Taher Zouaghi Editor), ISBN 978-953- 51-2886-1, InTech.
  • Nicolis, O. (2017). Wavelet-based multifractal analysis of Landsat-8 images: applications to mineral deposits and shale gas reservoirs. In Oil and Gas Exploration: Methods and Applica- tion (Saci, G. and Hachay, O., Eds.), John Wiley & Sons Inc. ISBN10 1119227429, ISBN13 9781119227427.
  • Nicolis, O. (2015) Environmental Smartcities: statistical mapping of environmental risk for natural and anthropic disasters in Chile. In: A. Fassò and A. Pollice (Editors). Proceedings of the GRASPA2015 Conference, Bari, 15-16 June, 2015. Special issue of GRASPA Working Papers. ISSN 2037-7738.
  • Nicolis, O., Nychka. D. (2012). Reduced Rank Covariances for the Analysis of Environmental Data. In Advanced Statistical Methods for the Analysis of Large Data-Sets (Di Ciacco, Coli, and Angulo Ibanez, eds.), Series: Studies in Theoretical and Apllied Statistics, Springer, ISBN 978-3-642-21036-5.
  • Derado, G., Lee, K., Nicolis, O., Bowman, F. D., Newell, M. Ruggeri F. and Vidakovic, B. (2008) Wavelet-based 3-D Multifractal Spectrum with Applications in Breast MRI Images. In Bioinformatics Research and Applications (Mandoiu, Sunderraman and Zelikovsky, eds.), Lecture Notes in Computer Science, Springer, 281-292.
  • Nicolis O., (2002) Wavelets e reti neurali: analisi e previsione dell’ozono. In Statistical Mon- itoring for Enviromental Engineering: Models and Applications to Bergamo county, Edited by R. Colombi and A. Fass`o, Bergamo University Press, Edizioni Sestante.
  • Nicolis O., Fassò A. (2002) Air quality in Bergamo area: a statistical descriptive analysis of the last decade. In Statistical Monitoring for Enviromental Engineering: Models and Applications to Bergamo county, Edited by R. Colombi and A. Fass`o, Bergamo University Press, Edizioni Sestante.

Artículos

  • Cavieres, J. and Nicolis, O. (2018) .Using a spatio-temporal Bayesian approach to estimate the relative abundance index of yellow squat lobster. Fisheries Research, Vol. 208, 97-104. DOI: 10.1016/j.fishres.2018.07.002.
  • Nicolis, O. and Pascual, R. (2018). A special issue on: Statistical methods in mining industry. Applied Stochastic Models in Business and Industry, Volume 34, Issue 3, 259–260. DOI: 10.1002/asmb.2339.
  • Stehlik, M., Polychronis, E., Papic, L., Aronov, J., Nicolis, O., Antoch, J., Cezova, E., Kisel ́ak, J. (2018). Statistical testing of availability for mining technological systems with air quality constraints. Applied Stochastic Models in Business and Industry, Volume 34, Issue 3, 278–292. DOI: 10.1002/asmb.2337.
  • Nava, D., Nicolis, O., Uribe-Opazo M.A., De Bastiani, F.(2018). Statistical methods for identifying anisotropy in the Spodoptera frugiperda spatial distribution. Spanish Journal of Agricultural Research, Vol. 16 (1), 1-10.
  • Salazar, L., Nicolis, O., Ruggeri, F., Kiseak, J., Stehlk, M. (2018). Predicting hourly ozone concentrations using wavelets and ARIMA models. Neural Computing and Applications, 1- 10.DOI: 10.1007/s00521-018-3345-0.
  • Nava, D. T. , De Bastiani, F., Uribe-Opazo, M. A., Nicolis, O., Galea, M. (2017). Local Influence for Spatially Correlated Binomial Data: An Application to the Spodoptera frugiperda Infestation in Corn.Journal of Agricultural, Biological and Environmental Statistics, Volume 22, Issue 4, pp 540561. DOI: 10.1007/ s13253-017-0306-5.
  • Nicolis, O., Kiselak, Porro, F., Stehl ́ ık, M., (2017). Multi-fractal cancer risk assessment. Stochastic Analysis and Applications, Vol. 35, 237-256.
  • Lillo, C. Leiva, V., Nicolis, O., Aykroyd, R. G. (2016). L-moments of the Birnbaum- Saunders distribution and its extreme value version: estimation, goodness of fit and application to earth- quake data Journal of Applied Statistics, 1-23, DOI: 10.1080/02664763.2016.1269729.
  • Stehl ́ık, M., Hermann, P., Nicolis, O.,(2016). Fractal based cancer modelling. REVSTAT – Statistical Journal 14 (2), 139-155.
  • Nicolis, O., Mateu, J. (2015). 2D Anisotropic Wavelet Entropy with an Application to Earthquakes in Chile. Entropy, 17(6), 4155-4172; doi:10.3390e17064155.
  • Nicolis, O., Mateu, J. (2015). Discussion of the paper “Analysis of Spatio-Temporal Mobile Phone Data: a Case Study in the Metropolitan Area of Milan”. Statistical Methods and Applications, 24, 315-319. DOI: 10.1007/s10260-015-0311-1.
  • Hermann, P., Mrkvicka, T., Mattfeldt, T., Minrov, M., Helisov, K., Nicolis, O. Wartner, F., Stehlk, M. (2015). Fractal and Stochastic Geometry Inference for Breast Cancer: Case Study with Random Fractals Models and Quermass-Interaction Process. Statistics in Medicine, 34 (18), 2636–2661. DOI: 10.1002sim.6497.
  • Nicolis, O., Chiodi, M, Adelfio, G. (2015). Windowed ETAS models with application to the Chilean seismic catalogs. Spatial Statistics, 14 (B) 151-165.DOI: 10.1016j.spasta.2015.05.006.
  • Mateu, J. and Nicolis, O. (2015). Multiresolution analysis of linearly-oriented spatial point patterns. Journal of Statistical Computation and Simulation. Vol. 85 (3), 621-637. DOI: 10.1080/00949655.2013.838565.
  • Deniz, E. and Nicolis, O. (2015) Genetic Algorithm in the Wavelet Domain for Large p Small n Regression. Communications in Statistics – Theory and Methods. Vo. 44(5) 1144-1157.
  • Remenyi N., Nicolis O., Nason G., and Vidakovic B. (2014). Image Denoising with 2-D Scale- Mixing Complex Wavelet Transforms. IEEE TRANSACTIONS ON IMAGE PROCESSING, Vol. 23 (12), 5165 – 5174.
  • Cressie, N., Assuncao, R., Holan, S., Levine, M., Nicolis, O., Zhang, J. and Zou, J. (2012). Dynamical Random-Set Modeling of Concentrated Precipitation in North America. Statistics and Its Interface, 5 (2), 169–182. ISSN: 1938-7989 (print); 1938-7997 (online)
  • Bagnato, L., Punzo, A., Nicolis, O. (2012). The autodependogram: a graphical device to investigate serial dependences. Journal of Time Series Analysis, 33 (2), 233–254. ISSN: 1467- 9892.
  • Nicolis, O., Ramirez, P. and Vidakovic, B. (2011). 2-D Wavelet-Based Spectra with Applica- tions. Computational Statistics and Data Analysis 55, 1, 738–751. ISSN: 0167-9473.
  • Sahu, S. K., Nicolis, O. (2008) An evaluation of European air pollution regulations for partic- ulate matter monitored from a heterogeneous network. Environmetrics. 20, (8), 943-961.
  • Fassò A., Cameletti M., Nicolis O. (2007) Air quality monitoring using heterogeneous networks. Environmetrics, 18: 245–264.
  • Mateu, J., Porcu, E. and Nicolis, O. (2006) A note on decoupling of local and global behaviour for the Dagum random field. Probabilistic Engineering Mechanics, 22, 320–329.
  • Nicolis, O., Tondini G. (2006) Logit models for analysing and forecasting the performance of industrial enterprises in the Treviso area. Managerial Finance, ISSN: 0307-4358, Volume: 32 Issue: 8 Page: 654 – 672.
  • Girardello P., Nicolis, O., Tondini G. (2003) Comparing conditional variance models: Theory and Empirical Evidence. Multinational Finance Journal, vol. 7, no. 3 & 4, pp. 177–206.
  • Nicolis, O., Lisi, L. , Sandri, M. (1995) Combining Singular-Spectrum Analysis and neural networks for time series forecasting, Neural Processing Letters, Volume 2, Number 4, July 1995.
  • Técnicas fractales para la exploración minera en la región metropolitana. FIC-2017, 2017-2018, FIC2017-Gobierno Regional de la Region Metropolitana. Investigador Responsable.
  • Spatio-temporal models for the analisis of air pollution and earthquakes, ID1131 147, 2013-2016, Fondecyt, Investigador Responsable.
  • Centro Interdisciplinario de Estudios Atmosfericos y Astroestadisticas Universidad de Valparaiso. 2015-2020, Universidad de Valparaiso. Investigador Responsable.
  • Methods for Integrating Renewable Energy Resources and Satellite Monitoring for Environmental Impacts. Italian National Research Comission, 2011, Co-Investigador.
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