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INFOSET  

Computing a New Informative Distribution Set of Asset Returns
View on CRAN: Click here


Download and install INFOSET package within the R console
Install from CRAN:
install.packages("INFOSET")

Install from Github:
library("remotes")
install_github("cran/INFOSET")

Install by package version:
library("remotes")
install_version("INFOSET", "4.1")



Attach the package and use:
library("INFOSET")
Maintained by
Gloria Polinesi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-09-05
Latest Update: 2024-11-23
Description:
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.
How to cite:
Gloria Polinesi (2024). INFOSET: Computing a New Informative Distribution Set of Asset Returns. R package version 4.1, https://cran.r-project.org/web/packages/INFOSET. Accessed 05 Jun. 2026.
Previous versions and publish date:
4.0.5 (2024-09-05 19:00), 4.0.6 (2024-09-06 15:00), 4.1 (2024-11-23 16:20)
Other packages that cited INFOSET R package
View INFOSET citation profile
Other R packages that INFOSET depends, imports, suggests or enhances
Complete documentation for INFOSET
Functions, R codes and Examples using the INFOSET R package
Full INFOSET package functions and examples
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