Tree Ring Analysis of Disturbance Events in R (TRADER) package provides functions for disturbance reconstruction from tree-ring data, e.g. boundary line, absolute increase, growth averaging methods.

Access 'Open Trade Statistics' API from R to download
    international trade data.

Contains performance analysis metrics of track records including entropy-based
            correlation and dynamic beta based on a state/space algorithm. The normalized sample entropy method
            has been implemented which produces accurate entropy estimation even on smaller datasets.
            On a separate stream, trades from the five major assets classes and also
            functionality to use pricing curves, rating tables, Credit Support Annex and add-on tables. The
            implementation follows an object oriented logic whereby each trade inherits from
            more abstract classes while also the curves/tables are objects. Furthermore, odds calculators
            and P&L back-testing functionality has been implemented for the most widely used betting/trading
            strategies including martingale, 'DAlembert', 'Labouchere' and Fibonacci. Back testing has also been included for the 'EuroMillions',
      			the 'EuroJackpot', the UK Lotto, the Set For Life and the UK 'ThunderBall' lotteries.
      			Furthermore, some basic functionality about climate risk has been included.

Estimate and return either the traffic speed or the car entries in the city of Thessaloniki using historical traffic data. It's used in transport pilot of the 'BigDataEurope' project. There are functions for processing these data, training a neural network, select the most appropriate model and predict the traffic speed or the car entries for a selected time date.

Tools for simulating and modeling traffic flow on road networks
    using spatial conditional autoregressive (CAR) models. The package
    represents road systems as graphs derived from 'OpenStreetMap' data 
    <https://www.openstreetmap.org/> and
    supports network-based spatial dependence, basic preprocessing, and
    visualization for spatial traffic analysis.