Maestría en Ciencia de Datos: Nasser Sadeghkhani

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Nasser Sadeghkhani

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52 55 5628 4000 ext. 3835
nasser@itam.mx

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Nasser Sadeghkhani es Profesor Asociado en el ITAM. Recibió su doctorado en Estadística de la Universidad de Sherbrooke, Canadá en el 2017. Además, fue becario postdoctoral en la Universidad de Queen’s (2017-2018) y en la Universidad de Brock (2018-2019).

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Intereses de investigación

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  • Estadística Bayesiana
  • Estadística Multivariada
  • Teoría de la Decisión
  • Inferencia Predictiva
  • Análisis de Datos Deportivos

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Publicaciones

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  •  Abdolnasser Sadeghkhani, Indranil Ghosh, A new generalized Balakrishnan type Skewed-Normal distribution: properties and associated inference. Communications in Statistics–Theory and Methods 2017. PDF.
  • Éric Marchand, Abdolnasser Sadeghkhani, On predictive density estimation with additional information, (2018) Electronic Journal of Statistics, 2018. PDF.
  • Abdolnasser Sadeghkhani, Yingwei Peng, and Devon Lin. A Parametric Bayesian Approach in Density Ratio Estimation. Stats 2019. PDF.
  • Abdolnasser Sadeghkhani , S. Ejaz Ahmed. Bayesian Predictive Densities as an Interpretation of a Class of Skew–Student t Distributions with Application to Medical Data. In: Xu J., Ahmed S., Cooke F., Duca G. (eds) Proceedings of the Thirteenth International Conference on Management Science and Engineering Management. ICMSEM 2019. Advances in Intelligent Systems and Computing, vol 1001. Springer, Cham.
  • Abdolnasser Sadeghkhani, S. Ejaz Ahmed. A Bayesian Approach to Predict the Number of Goals in Hockey. Stats 2019. PDF.
  • Abdolnasser Sadeghkhani, S. Ejaz Ahmed. Predicting the scoring time in hockey (submitted).
  • Abdolnasser Sadeghkhani, S. Ejaz Ahmed. The Application of Predictive Density Estimation in Multiple-Inflated Poisson Models to Ice Hockey Data (submitted).
  • Abdolnasser Sadeghkhani, Ali Sadeghkhani. A comprehensive study to the Benini distribution: An application in modeling catastrophic hurricane losses (submitted).
  • Abdolnasser Sadeghkhani, An alternative to the exponential power distribution (submitted).
  • Abdolnasser Sadeghkhani, S. Ejaz Ahmed, On predictive density estimation of K–inflated Poisson models with additional information. (submitted)

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Cursos

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  • Fundamentos de Estadística
  • Estadística Multivariada y Datos Categóricos
  • Estadística Matemática

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El programa de la Maestría en Ciencia de Datos es una iniciativa del ITAM para satisfacer la creciente demanda nacional e internacional de profesionistas con conocimientos sólidos en el modelado a partir de datos (en especial grandes datos) para ayudar a la toma de decisiones estratégicas.

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