Data Analysis in R, Part One, by George Vega Yon. This session will be divided in three sessions and will include theory and application of social networks statistical models in R and spatial econometrics:
1st Block, Motivation:
(a) When data isn’t IID.
(b) Models families: Graphos vs. behavior.
2nd Block, Network models:
(a) ERGMs and variations: MERGMs, TERGMs, SERGMs, Relational Event Models, ERGMitos, etc.
(b) Latent networks.
(c) SOAM and others.
(d) Network models estimate: Estimation diagnostics, convergence.
(e) Non parametrics models: matching and permutation.
3rd Block, Spatial Econometrics:
(a) Spatial autoregresive models: description, assumptions, etc.
(b) Family of models: Heteroscedasticity, autocorrelated mistakes, IV sol and estimate methods, SARAR, SAR Probit/Logit/MLogit
Bio: George G. Vega Yon, PhD student in Biostatistics in the University of South California, USA. Master in Sciences, California Institute of Technology (Caltech, USA), Master in Economics and Public Policies, Adolfo Ibáñez University, Chile. His research interests are computational statistics applied to the modelling of biological and socio-technical systems, as evolution from genetical functions and social networks.
Date: Thursday, December 20th, from 10.00 to 13.00.
Place: Room C201, Building Edificio, Campus San Joaquín, Pontificia Universidad Católica (Vicuña Mackenna 4860, Macul. Metro San Joaquín, Santiago).