by Oscar Perpiñán Lamigueiro Introduction A time series is a sequence of observations registered at consecutive time instants. The visualization of time series is intended to reveal changes of one or more quantitative variables through time, and to display the relationships between the variables and their evolution through time. ...

by Jorge Cimentada Introduction Whenever a new paper is released using some type of scraped data, most of my peers in the social science community get baffled at how researchers can do this. In fact, many social scientists can’t even think of research questions that can be addressed with ...

by María Medina Pérez According to CIS’ barometer, political corruption is the second biggest concern in Spain, only behind unemployment, and has been in this position since 2013, as we see Spanish news talking about open trials and new investigations on a regular basis. The European Commission estimates that ...

by Carlos J. Gil Bellosta Big datasets found in statistical practice often have a rich structure. Most traditional methods, including their modern counterparts, fail to efficiently use the information contained in them. Here we propose and discuss an alternative modelling strategy based on herds of simple models. Big Data: How ...

by Virginia Peón García You test your code. We know you do. How else are you sure that your changes don’t break the program? But after you commit, you discard those pesky scripts and throw away code. Don’t you think it’s a bit of a ...

by Virgilio Gómez Rubio Introduction In this session I will focus on Bayesian inference using the integrated nested Laplace approximation (INLA) method. As described in Rue et al. (2009), INLA can be used to estimate the posterior marginal distribution of Bayesian hierarchical models. This method is implemented in the INLA ...

by Antonio Sánchez Learning to code can be quite hard. Apart from the difficulties of learning a new language, following a book can be quite boring. From my point of view, one of the bests ways to become a good programmer is choosing small and funny experiments oriented to ...

by Paula LC Do you want to know how to make elegant and simple reproducible presentations? In this talk, we are going to explain how to do presentations in different output formats using one of the easiest and most exhaustive statistical software, R. Now, it is possible create Beamer, PowerPoint, ...

by Mariluz Congosto Network analysis offers a perspective of the data that broadens and enriches any investigation. Many times we deal with data in which the elements are related, but we have them in a tabulated format that is difficult to import into network analysis tools. Relationship data require a ...

Stan is a probabilistic programming language for specifying statistical models. Stan provides full Bayesian inference for continuous-variable models through Markov Chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited ...

The aim of this tutorial is to show the use of TensorFlow with KERAS for classification and prediction in Time Series Analysis. The latter just implement a Long Short Term Memory (LSTM) model (an instance of a Recurrent Neural Network which avoids the vanishing gradient problem). Introduction The code below ...

In this session I will try to show some utilities present in the web. One of them will help us to execute R code from the web, using an online compiler, without installing any kind of software in our computers. The other one, it can help us to solve optimization ...

This is our second session introducing Shiny, an R package that allows to develop interactive Apps in a familiar framework for regular R-users. During the first session we focused on the structure and workflow basics, and now, we will go further on input and output objects, reactivity, layouts and data ...

Tensorflow has been widely used for many applications in machine learning and deep learning. However, Tensorflow is more than that, it is a general purpose computing library. Based on that, people have created a rich ecosystem for quickly developing models. In this talk, I will show how statisticians can get ...