Title: Access to RFR (Risk-Free Rate) Curves Produced by the EIOPA
Description: Provides EIOPA (European Insurance And Occupational Pensions Authority) risk-free rates. Please note that the author of this package is not affiliated with EIOPA. The data is accessed through a REST API available at <https://mehdiechchelh.com/api/>.
Collate: 'const.R' 'api.R' 'eiopaR.R' 'utils.R'

Packaged: 2021-05-31 06:11:26 UTC; mehdi.echchelh

Title: Explanatory Item Response Modeling for Dichotomous and
person("Okan", "Bulut", email = "bulut@ualberta.ca", role = c("aut", "cre"),
Description: Analysis of dichotomous and polytomous response data using the explanatory item response modeling framework, as described in Stanke & Bulut (2019) <doi:10.21449/ijate.515085> and De Boeck & Wilson (2004) <doi:10.1007/978-1-4757-3990-9>. Generalized linear mixed modeling is used for estimating the effects of item-related and person-related variables on dichotomous and polytomous item responses.
Author: Okan Bulut [aut, cre] (<https://orcid.org/0000-0001-5853-1267>)

Imports: magrittr, shiny, shinydashboard, shinycssloaders, readxl

Imports: magrittr, shiny, shinydashboard, shinycssloaders, readxl,

Description: Analysis of dichotomous and polytomous response data using the explanatory item response modeling framework, as described in Bulut, Gorgun, & Yildirim-Erbasli (2021) <doi:10.3390/psych3030023>, Stanke & Bulut (2019) <doi:10.21449/ijate.515085>, and De Boeck & Wilson (2004) <doi:10.1007/978-1-4757-3990-9>. Generalized linear mixed modeling is used for estimating the effects of item-related and person-related variables on dichotomous and polytomous item responses.

Title: An algorithm for reducing errors-in-variable bias in simple
Author: Mehmet Hakan Satman (PhD), Erkin Diyarbakirlioglu (PhD)
Description: EIVE performs a compact genetic algorithm search to reduce
errors-in-variables bias in linear regression.

Description: EIVE performs a compact genetic algorithm search to reduce errors-in-variables bias in linear regression.