Packaged: 2022-04-09 09:00:44 UTC; Mario Grassi

Packaged: 2022-07-05 16:29:01 UTC; Mario Grassi

Grassi M, Palluzzi F, Tarantino B (2022) <doi:10.1093/bioinformatics/btac567>.
Packaged: 2022-10-12 08:27:47 UTC; Mario Grassi

Title: R Interface to Access the 'SEMrush' API
Authors@R: person("Remi", "Bacha", email = "hello@remibacha.com", role = c("aut", "cre"))
Description: Implements methods for querying SEO (Search Engine Optimization) and SEM (Search Engine Marketing) data from 'SEMrush' using its API (<https://fr.semrush.com/api-documentation/>).
'SEMrush' API uses a basic authentication with an API key.

Title: A Tool for Sensitivity Analysis in Structural Equation Modeling
Description: Perform sensitivity analysis in structural equation modeling using
meta-heuristic optimization methods (e.g., ant colony optimization and others).
The references for the proposed methods are:
(1) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017)
We also thank Dr. Krzysztof Socha for sharing his thesis and R code,
which provided the base for the development of this package.

person("Walter", "Leite", email = "walter.leite@coe.ufl.edu", role = c( "aut", "cre")),
person("YongSeok", "Lee", role = "ctb"),
person("Sanaz", "Nazari", role = "ctb"),
(1) Leite, W., & Shen, Z., Marcoulides, K., Fish, C., & Harring, J. (in press).
Using ant colony optimization for sensitivity analysis in
Structural Equation Modeling: A Multidisciplinary Journal.
(2) Harring, J. R., McNeish, D. M., & Hancock, G. R. (2017)
We also thank Dr. Krzysztof Socha for sharing his research on ant colony optimization
algorithm with continuous domains and associated R code,

person("Charles", "Fisk", role = "aut"),
(1) Leite, W., & Shen, Z., Marcoulides, K., Fish, C., & Harring, J. (2022).
(3) Fisk, C., Harring, J., Shen, Z., Leite, W., Suen, K., & Marcoulides, K.

person("King Yiu", "Suen", role = "aut"),
person("Katerina", "Marcoulides", role = "aut"),

Title: Spiked Eigenvalue Test for Pathway data
Description: Tests gene expression data from a biological pathway for biologically meaningful differences in the eigenstructure between two classes.  Specifically, it tests the null hypothesis that the two classes' leading eigenvalues and sums of eigenvalues are equal.  A pathway's leading eigenvalue arguably represents the total variability due to variability in pathway activity, while the sum of all its eigenvalues represents the variability due to pathway activity and to other, unregulated causes. Implementation of the method described in Danaher (2015), "Covariance-based analyses of biological pathways".