This final post about the STAN platform will specifically focus on data visualizations that can come from STAN models. In particular, we will explore these visualizations by hand with the popular shinystan package. As we already know, the STAN platform typically uses particular Markov Chain Monte Carlo (MCMC) algorithms: the Hamiltonian Monte Carlo (HMC) or […]
Exercises
How to Plot With Metricsgraphics: Exercises
INTRODUCTION Metricsgraphics is an htmlwidget interface to the MetricsGraphics.js JavaScript/D3 chart library. Usage Building metricsgraphics charts follows the “piping” idiom, made popular through the magrittr, ggvis and dplyr packages. This makes it possible to avoid one giant function with a ton of parameters and facilitates, breaking out the chart and building into logical steps. While […]
R FOR HYDROLOGISTS – Seasonality and Trend Decomposition
R FOR HYDROLOGISTS SEASONALITY AND TREND DECOMPOSITION If you don’t have the data, please first get it from the first tutorial here. Also, you need to install and load the ggplot2 package. if(!require(ggplot2)){install.packages(ggplot2, dep=T)} Answers to these exercises are available here. Time series decomposition is a mathematical procedure which transforms a time series into multiple different […]
Applied Economic Analysis With R – Part 1: Exercises
R has great potential in Economic data analysis, as well as econometrics. In this set of exercises, we will go through a wide variety of topics in econometrics, including wage equations, growth regressions, dynamic regressions and time series models, hedonic regressions, the demand for health care, and labor force participation. In the first set of […]
K-Means Clustering in R – Exercises
K-means is efficient, and perhaps, the most popular clustering method. It is a way for finding natural groups in otherwise unlabeled data. You specify the number of clusters you want defined and the algorithm minimizes the total within-cluster variance. In this exercise, we will play around with the base R inbuilt k-means function on some labeled […]
Parsing Dates and Time – Part 2: Exercises
In the exercises below, we will continue working with lubridate and examine more features of the library. Answers to these exercises are available here. Please check the previous exercise here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on […]
How to Visualize Data With Highcharter: Exercises
INTRODUCTION Highcharter is an R wrapper for Highcharts’ JavaScript library and its modules. Highcharts is very mature and flexible on JavaScript’s charting library. It has a great and powerful API. Before proceeding, please follow our short tutorial. Look at the examples given and try to understand the logic behind them. Then, try to solve the […]
MCMC Using STAN – Diagnostics With The Bayesplot Package: Exercises
This exercise set will continue to present the STAN platform, but with another useful tool: the bayesplot package. This package is very useful to construct diagnostics that can be used to have insights on the convergence of the MCMC sampling since the convergence of the generated chains is the main issue in most STAN models. […]
Simple Numerical Modeling in R – Part 2: Exercises
In this exercise, we will continue to build our model from our previous exercise here, specifically to revise the errors that may be generated from the model, including rounding and truncating errors. Answers to these exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel […]
Advanced Raster Data: Exercises
Geospatial data is becoming increasingly used to solve numerous ‘real-life’ problems (check out some examples here.) In turn, R is becoming a powerful open-source solution to handle this type of data, currently providing an exceptional range of functions and tools for GIS and Remote Sensing data analysis. In particular, raster data provides support for representing […]
