Datasets from Yotov, et al. (2016, ISBN:978-92-870-4367-2) "An
    Advanced Guide to Trade Policy Analysis" and functions to report regression
    summaries with clustered robust standard errors.

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 the Kalman filter. The normalized sample entropy method
            has been implemented which produces accurate entropy estimation even on smaller datasets while for
            the dynamic beta calculation the Kalman filter methodology has been utilized.
            On a separate stream, trades from the five major assets classes and also
            functionality to use pricing curves, rating tables, CSAs 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 and EuroJackpot 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.

Estimation, selection and comparison of several families of
 transformations. The families of transformations included in the package are 
 the following: Bickel-Doksum (Bickel and Doksum 1981 <doi:10.2307/2287831>), 
 Box-Cox, Dual (Yang 2006 <doi:10.1016/j.econlet.2006.01.011>), 
 Glog (Durbin et al. 2002 <doi:10.1093/bioinformatics/18.suppl_1.S105>), 
 gpower (Kelmansky et al. 2013 <doi:10.1515/sagmb-2012-0030>), 
 Log, Log-shift opt (Feng et al. 2016 <doi:10.1002/sta4.104>),
 Manly, modulus (John and Draper 1980 <doi:10.2307/2986305>), 
 Neglog (Whittaker et al. 2005 <doi:10.1111/j.1467-9876.2005.00520.x>), 
 Reciprocal and Yeo-Johnson. The package simplifies to 
 compare linear models with untransformed and transformed dependent variable 
 as well as linear models where the dependent variable is transformed with 
 different transformations. Furthermore, the package employs maximum likelihood 
 approaches, moments optimization and divergence minimization to estimate the optimal 
 transformation parameter.