Suggests: RUnit, knitr, BiocStyle, rmarkdown, BiocGenerics

Author: Andrea Rodriguez-Martinez, Rafael Ayala, Mark Balchunas, Yacine Debbabi, Lara Selles Vidal
Description: Provides a tool set for food information and dietary assessment. It
uses food composition data from several reference databases, including: 'USDA' (United States),
'CIQUAL' (France), and 'BEDCA' (Spain). 'NutrienTrackeR' calculates the intake levels for both
macronutrient and micronutrients, and compares them with the recommended dietary allowances (RDA).
It includes a number of visualization tools, such as time series plots of nutrient intake,
and pie-charts showing the main foods contributing to the intake level of a given nutrient.
A shiny app exposing the main functionalities of the package is also provided.

'CIQUAL' (France), 'BEDCA' (Spain) and 'CNF' (Canada). 'NutrienTrackeR' calculates the intake
levels for both macronutrient and micronutrients, and compares them with the recommended
dietary allowances (RDA). It includes a number of visualization tools, such as time series
plots of nutrient intake, and pie-charts showing the main foods contributing to the intake
level of a given nutrient. A shiny app exposing the main functionalities of the package is also
Packaged: 2021-11-14 11:16:49 UTC; rafael-ayala

Title: Harvest Metadata Using OAI-PMH v2.0
Harvest metadata using the Open Archives Initiative Protocol for Metadata
Packaged: Tue Mar  3 08:55:34 2009; hornik

Packaged: Thu Mar  5 09:13:00 2009; hornik

Description: Harvest metadata using the Open Archives Initiative
Protocol for Metadata Harvesting (OAI-PMH) version 2.0.
Packaged: Sat Mar 14 16:56:36 2009; hornik

Authors@R: person("Kurt", "Hornik", role = c("aut", "cre"), email =

Title: Harvest Metadata Using OAI-PMH Version 2.0
Harvesting (OAI-PMH) version 2.0 (for more information, see

Title: Objective Bayesian Analysis for Spatial Regression Models
Author: Alejandro Ordonez,  Marcos O. Prates , Larissa A. Matos, Victor H. Lachos.
Description: It makes an objective Bayesian analysis of the spatial regression model using both the normal (NSR) and student-T (TSR) distributions. The functions provided give prior and posterior objective densities and allow default Bayesian estimation of the model regression parameters. Details can be found in Ordonez et al. (2020) <arXiv:2004.04341>.