Explore the influential factors on H-1B data
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Updated
Mar 13, 2017 - R
Explore the influential factors on H-1B data
Statistical Analysis of Real Estate Prices in Ames, IA
Bayesian inference for everyday tasks
Bayesian multilevel modeling of real estate sales in NYC
SJSU-Projects are those projects I applied machine learning algorithms or statistical methods on real data sets.
An introduction to hierarchical Bayesian modelling with R, JAGS and STAN
This section is for my latex project repport :
R package. Bayesian linear model in a time series context (dynamic beta for each observation). Uses RStan to develop the MCMC algorithm. Author: Carlos Omar Pardo Gomez.
Code for analysis of soils, crops, and nutrition along a distance-to-forest gradient in Ethiopia
Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.
Applied analysis on the Bayesian student-t "Robust" regression model with Jeffrey's prior. Compared its model performance and robustness of posterior distributions with the Gaussian model when outliers are present.
Bayesian Network Learning in R
Bayesian linear model in R
Spatial and Spatio-Temporal Bayesian Model for Circular Data
This unit provides a strong background in the analysis of multivariate and categorical data. Concepts such as probability theory, Bayesian modelling, dimensionality reduction, clustering, finite mixture modelling and probabilistic graphical models form the core knowledge of this unit.
R Package. Bayesian and nonparametric quantile regression, using Gaussian Processes to model the trend, and Dirichlet Processes, for the error. Author: Carlos Omar Pardo Gomez.
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