Simulation, Estimation and Segmentation of Composite Based
Structural Equation Models
The composites are linear combinations of their indicators in composite based structural equation models. Structural models are considered consisting of two blocks. The indicators of the exogenous composites are named by X, the indicators of the endogenous by Y. Reflective relations are given by arrows pointing  from the composite to their indicators. Their values are called loadings.  In a reflective-reflective scenario all indicators have loadings. Arrows are pointing to their indicators only from the endogenous composites in  the formative-reflective scenario. There are no loadings at all in the formative-formative scenario. The covariance matrices are computed for these three scenarios. They can be used to simulate these models. These models can also be estimated and a segmentation procedure is included as well.

Statistics Netherlands (CBS) Open Data API Client
The data and meta data from Statistics
Netherlands (www.cbs.nl) can be browsed and downloaded. The client uses
the open data API of Statistics Netherlands.

c(person("Edwin", "de Jonge", email="edwindjonge@gmail.com", role = c("aut","cre")))

c(person("Edwin", "de Jonge", email="edwindjonge@gmail.com", role = c("aut","cre")),
person("Sara", "Houweling", role=c("ctb")))
The data and meta data from Statistics
Netherlands (<https://www.cbs.nl>) can be browsed and downloaded. The client uses
the open data API of Statistics Netherlands.
Edwin de Jonge [aut, cre],
Sara Houweling [ctb]

knitr, rmarkdown, dplyr, shiny, testthat (>= 2.1.0)

ccChooser can be used to developing and evaluation of core
collections for germplasm collections (entire collection). This
package used to develop a core collection for biological
resources like genbanks. A core collection is defined as a
sample of accessions that represent, with the lowest possible
level of redundancy, the genetic diversity (the richness of
gene or genotype categories) of the entire collection. The
establishing a core collection that represents genetic
diversity of the entire collection with minimum loss of its
original diversity and minimum redundancies is an important
problem for gene-banks curators and crop breeders. ccChooser
establish core collection base on phenotypic data (agronomic,
morphological, phenological).