Chain Event Graph (ceg)
Create and learn Chain Event Graph (CEG) models using a Bayesian framework. It provides us with a Hierarchical Agglomerative algorithm to search the CEG model space. The package also includes several facilities for visualisations of the objects associated with a CEG. The CEG class can represent a range of relational data types, and supports arbitrary vertex, edge and graph attributes. A Chain Event Graph is a tree-based graphical model that provides a powerful graphical interface through which domain experts can easily translate a process into sequences of observed events using plain language. CEGs have been a useful class of graphical model especially to capture context-specific conditional independences. References: Collazo R, Gorgen C, Smith J. Chain Event Graph. CRC Press, ISBN 9781498729604, 2018 (forthcoming); and Barday LM, Collazo RA, Smith JQ, Thwaites PA, Nicholson AE. The Dynamic Chain Event Graph. Electronic Journal of Statistics, 9 (2) 2130-2169 <doi:10.1214/15-EJS1068>.

Project Future Case Incidence (projections)
Provides functions and graphics for projecting daily incidence based on past incidence, and estimates of the serial interval and reproduction number. Projections are based on a branching process using a Poisson-distributed number of new cases per day, similar to the model used for estimating R0 in ‘EpiEstim’ or in ‘earlyR’, and described by Nouvellet et al. (2017) <doi:10.1016/j.epidem.2017.02.012>.

Frequent Pattern Mining Outliers (fpmoutliers)
Algorithms for detection of outliers based on frequent pattern mining. Such algorithms follow the paradigm: if an instance contains more frequent patterns, it means that this data instance is unlikely to be an anomaly (He Zengyou, Xu Xiaofei, Huang Zhexue Joshua, Deng Shengchun (2005) <doi:10.2298/CSIS0501103H>). The package implements a list of existing state of the art algorithms as well as other published approaches: FPI, WFPI, FPOF, FPCOF, LFPOF, MFPOF, WCFPOF and WFPOF.

A Menu-Driven GUI for Analyzing and Modelling Data of Just Finance and Econometrics (JFE)
The Just Finance and Econometrics (‘JFE’) provides a ‘tcltk’ based interface to global assets selection and portfolio optimization. ‘JFE’ aims to provide a simple GUI that allows a user to quickly load data from a .RData (.rda) file, explore the data and evaluate financial models. Invoked as JFE(), ‘JFE’ exports a number of utility functions for visualizing assets price (e.g. technical charting) and returns, selecting assets by performance index (based on the package ‘PerformanceAnalytics’) and backtesting specific portfolio profiles (based on the package ‘fPortfolio’).

Continuous Counterfactual Analysis (ccfa)
Contains methods for computing counterfactuals with a continuous treatment variable as in Callaway and Huang (2017) <>. In particular, the package can be used to calculate the expected value, the variance, the interquantile range, the fraction of observations below or above a particular cutoff, or other user-supplied functions of an outcome of interest conditional on a continuous treatment. The package can also be used for computing these same functionals after adjusting for differences in covariates at different values of the treatment. Further, one can use the package to conduct uniform inference for each parameter of interest across all values of the treatment, uniformly test whether adjusting for covariates makes a difference at any value of the treatment, and test whether a parameter of interest is different from its average value at an value of the treatment.

Interpretive Structural Modelling (ISM) (ISM)
The development of ISM was made by Warfield in 1974. ISM is the process of collaborating distinct or related essentials into a simplified and an organized format. Hence, ISM is a methodology that seeks the interrelationships among the various elements considered and endows with a hierarchical and multilevel structure. To run this package user needs to provide a matrix (VAXO) converted into 0’s and 1’s. Warfield,J.N. (1974) <doi:10.1109/TSMC.1974.5408524> Warfield,J.N. (1974, E-ISSN:2168-2909).