Rafaél Artidoro Sandoval Núñez
My blogs
| Gender | Male |
|---|---|
| Industry | Education |
| Occupation | Degree in Statistics, Universidad Nacional Pedro Ruiz Gallo, Lambayeque, Peru; Master in Mathematics with Mention in Statistics, Universidad del Bio-Bio, Concepcion, Chile. |
| Location | Lima , Lima , Peru |
| Interests | Time Series Analysis, Generalized Linear Models, Multivariate Analysis, Robust Linear Models, Experimental design, Demography, Biostatistics, Sampling, Ocean-Atmosphere Interaction, Econometrics, Statistical Programming, Bioinformatics, R Project, SAS, STATA, ORACLE, SQL, Python, VBA Macro, Databases, MS Excel, MATLAB, LaTeX, Windows, Mac OS X, Linux. |
| Favorite Movies | Animation, Comedy, Drama, Action, Science Fiction, Romance and Suspense. |
| Favorite Music | Salsa, Bachata, Merengue and Cumbia. |
| Favorite Books | Box et al. Time series analysis: Forecasting and control (2016), Palma W. Time series analysis (2016), Palma W. (2007). Long-memory time series: theory and methods (2007), Tsay R. Multivariate time series analysis: With R and financial applications (2014), Brockwell and Davis. Introduction to time series and forecasting (2016), Commandeur and Koopman. An introduction to state space time series analysis (2007), Madsen H. Time series analysis (2008), Durbin and Koopman. Time series analysis by state space methods (2012), Lütkepohl H. New introduction to multiple time series analysis (2007), Dobson A. An Introduction to Generalized Linear Models (2008), Hosmer et al. Applied logistic regression (2013), James et al. An introduction to statistical learning: With applications in R (2015), Cameron and Trivedi Regression analysis of count data (2013), Faraway Linear models with R (2015), Faraway Extending the linear model with R: Generalized linear mixed effects and nonparametric regression models (2016), Kutner et al. Applied linear statistical models (2005), Berridge et al. Multivariate generalized linear mixed models using R (2011), Yan et al. Linear regression analysis: Theory and computing (2009), Peng R. R Programming for data science (2016), Peng R. Exploratory Data Analysis with R (2015), Caffo B. Statistical inference for data science. |