Bayesian statistics and methods

Good resources for bayesian statistics:

http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/#contents        for python

https://onlinecourses.science.psu.edu/stat414/node/241

http://www.r-bloggers.com/r-and-bayesian-statistics/

http://stats.stackexchange.com/questions/74082/what-is-the-difference-in-bayesian-estimate-and-maximum-likelihood-estimate

http://stats.stackexchange.com/questions/73439/comparing-maximum-likelihood-estimation-mle-and-bayes-theorem/73470#73470

http://stats.stackexchange.com/questions/58564/help-me-understand-bayesian-prior-and-posterior-distributions/58792#58792

http://arxiv.org/pdf/0804.2996.pdf       The Epic Story of Maximum Likelihood

http://stats.stackexchange.com/questions/11109/how-to-deal-with-perfect-separation-in-logistic-regression

http://projecteuclid.org/download/pdfview_1/euclid.aoas/1231424214

Time series with R

Interesting places to know about how to manage time series with R:

http://www.statmethods.net/advstats/timeseries.html

http://cran.r-project.org/web/views/TimeSeries.html

http://cran.r-project.org/doc/contrib/Ricci-refcard-ts.pdf

http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf

https://www.otexts.org/fpp    a classic

http://a-little-book-of-r-for-time-series.readthedocs.org/en/latest/    seems very good

http://www.stat.pitt.edu/stoffer/tsa3/   the starting point url for the following books

http://www.stat.pitt.edu/stoffer/tsa3/tsa3.pdf      extensive

http://www.stat.pitt.edu/stoffer/tsa3/tsa3EZ.pdf    a short version of the above

http://www.stat.pitt.edu/stoffer/nltsa/   non linear time series