All you need is love and R

R
Intercative Communication
Lecture Notes
Published

December 11, 2021

Meetup Description

Michela Cameletti from the University of Bergamo talks about academic (teaching and research) activities for which R is used. As an academician, Michela has used R in many ways.

The packages she uses the most

Data manipulation and plotting:

  • standard `R` code and objects

  • `tidyverse` collection

Spatial objects manipulation and mapping:

  • `rgdal`, `spdep`, `sp`, `sf`, `lattice`, `fields`, `maptools`, `leaflet`, …

Modelling:

  • `R-INLA`, `rpart`, …

Parallel computing:

  • `parallel`, `snow`, …

a) Interactive research communication

Some of her interactive research communication includes her Shiny app link from her research paper A spatio-temporal analysis of NO2 concentrations during the Italian 2020 COVID-19 lockdown.

Spatio temporal shiny app screenshot

b) Interactive research communication

Her other work on Regional excess mortality during the 2020 COVID-19 pandemic: a study of five European countries, uses data for 2015-2019 to apply Bayesian spatio-temporal models to quantify the expected weekly deaths at the regional level had the pandemic not occurred in England, Greece, Italy, Spain, and Switzerland. The shiny app estimates the excess mortality caused by the COVID-19 pandemic during 2020 in five European countries: England, Greece, Italy, Spain and Switzerland.


Lab notes example

The notes posted online for her students can be accessed anywhere there is internet connectivity. See the labs’ notes for the Machine Learning for Economics. The course notes were created using Bookdown. An open-source R package?that facilitates writing books and long-form articles/reports with R Markdown.


Stem package

Note

Unfortunately, the Stem package that was developed by Michela has been removed from CRAN. However, the last documentation can be seen at R documentation.

This package focused on spatio-temporal hierarchical models. The package includes functions for maximum likelihood estimation (based on Kalman filtering and EM algorithm), for computing the parameter standard errors (using a parametric spatio-temporal bootstrap) and for spatial mapping.

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