Creates a contextual menu that can be triggered with keyboard shortcuts or programmatically.
    This can replace traditional sidebars or navigation bars, thereby enhancing the 
    user experience with lighter user interfaces.

Using principal component analysis as a base model, 'SCOUTer' 
    offers a new approach to simulate outliers in a simple and precise way. 
    The user can generate new observations defining them by a pair of well-known 
    statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) 
    statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' 
    returns a new set of observations with the desired target properties. 
    Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and 
    Alberto Ferrer (2020).

Implements estimators for structured covariance matrices in the
    presence of pairwise and spatial covariates.
    Metodiev, Perrot-Dockès, Ouadah, Fosdick, Robin, Latouche & Raftery (2025)
    <doi:10.48550/arXiv.2411.04520>.

Implements different inventory models, the bullwhip effect and other supply chain performance variables. Marchena Marlene (2010) <arXiv:1009.3977>.

R version of 'scperturb' tool for single-cell perturbation 
    analysis. Contains wrappers for performing E-statistics for Seurat objects. 
    More details on the method can be found in Peidli et al. (2023) 
    <doi:10.1101/2022.08.20.504663> and in Székely and Rizzo (2004).

Implementation of prediction and inference procedures for Synthetic Control methods using least square, lasso, ridge, or simplex-type constraints. Uncertainty is quantified with prediction intervals as developed in Cattaneo, Feng, and Titiunik (2021) <doi:10.1080/01621459.2021.1979561> for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2025) <doi:10.1162/rest_a_01588> for multiple treated units and staggered adoption. More details about the software implementation can be found in Cattaneo, Feng, Palomba, and Titiunik (2025) <doi:10.18637/jss.v113.i01>.