Package: genpathmox
Title: Generalized Pathmox Approach Segmentation Tree Analysis
Version: 0.5
Authors@R: person("Giuseppe", "Lamberti", email = "giuseppelamb@hotmail.com",
role = c("aut", "cre"))
Description: Provides a very interesting solution for
handling segmentation variables in complex statistical methodology. It
contains en extended version of the "Pathmox" algorithm (Lamberti, Sanchez
and Aluja,(2016)<doi:10.1002/asmb.2168>) in the context of
Partial Least Squares Path Modeling including the F-block
test (to detect the responsible latent endogenous equations of the
difference), the F-coefficient (to detect the path coefficients responsible
of the difference) and the "invariance" test (to realize a comparison
between the sub-models' latent variables). Furthermore, the package
contains a generalized version of the "Pathmox" algorithm to approach
different methodologies: linear regression and least absolute regression
models.
Depends: R (>= 3.1.2), stats, graphics, grDevices, utils, diagram,
methods, quantreg
License: GPL-3
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-16 09:43:14 UTC; giuseppelamberti
Author: Giuseppe Lamberti [aut, cre]
Maintainer: Giuseppe Lamberti <giuseppelamb@hotmail.com>
Repository: CRAN
Date/Publication: 2020-11-16 10:00:03 UTC

Description: It provides an interesting solution for handling a high number
of segmentation variables in partial least squares structural equation
modeling. The package implements the "Pathmox" algorithm (Lamberti, Sanchez,
and Aluja,(2016)<doi:10.1002/asmb.2168>) including the F-coefficient
test (Lamberti, Sanchez, and Aluja,(2017)<doi:10.1002/asmb.2270>)
to detect the path coefficients responsible for the identified differences),
the hybrid multi-group approach (Lamberti (2021)
approaches (parametric and permutation approaches). The package also
includes an extension of the "Pathmox" algorithm to the case of
Packaged: 2021-02-17 20:12:47 UTC; giuseppelamberti

Packaged: 2021-08-12 11:14:55 UTC; giuseppelamberti

Title: Pathmox Approach Segmentation Tree Analysis
to detect the path coefficients responsible for the identified differences).
The package also allows running the hybrid multi-group approach (Lamberti (2021)
Depends: R (>= 3.5.0), stats, cSEM, diagram, methods, graphics,
Packaged: 2022-05-05 12:52:30 UTC; giuseppelamberti