Estimation of the most-left informative set of gross returns 
             (i.e., the informative set).
             The procedure to compute the informative set adjusts the method 
             proposed by 
             Mariani et al. (2022a) <doi:10.1007/s11205-020-02440-6> 
             and 
             Mariani et al. (2022b) <doi:10.1007/s10287-022-00422-2> 
             to gross returns of financial assets. 
             This is accomplished through an adaptive algorithm
             that identifies sub-groups of gross returns in 
             each iteration by approximating their distribution with a
             sequence of two-component log-normal mixtures. 
             These sub-groups emerge when a significant change
             in the distribution occurs below the median of the 
             financial returns, with their boundary termed as
             the “change point" of the mixture. 
             The process concludes when no further change points are detected.
             The outcome encompasses parameters of the leftmost mixture 
             distributions and change points of the
             analyzed financial time series.
             The functionalities of the INFOSET package include: (i) modelling asset distribution
             detecting the parameters which describe left tail behaviour (infoset function), (ii) clustering, (iii) labeling of the financial
             series for predictive and classification purposes through a Left Risk measure based on the first change point (LR_cp function)
             (iv) portfolio construction (ptf_construction function).
             The package also provide a specific function to construct rolling windows of different length size and overlapping time.

Implements the Information Matrix test for regression models following Cameron, A. C., & Trivedi, P. K. (1990) <https://cameron.econ.ucdavis.edu/research/imtest_impliedalternatives_ucdwp372.pdf> Decomposes the test into components for heteroscedasticity, skewness, and kurtosis to diagnose specific forms of misspecification. Provides both overall and component-wise statistics for model assessment.