Title: Traffic Predictions Using Neural Networks
Description: Estimate and return either the traffic speed or the car entries in the city of Thessaloniki using historical traffic data. It's used in transport pilot of the 'BigDataEurope' project. There are functions for processing these data, training a neural network, select the most appropriate model and predict the traffic speed or the car entries for a selected time date.
Authors@R: c(person("Kleanthis", "Koupidis", role = c("aut", "cre"),
person("Aikaterini", "Chatzopoulou", role = "aut",
Imports: caret, data.table, DescriptiveStats.OBeu, dplyr, lubridate,
Suggests: devtools, knitr, neuralnet, rmarkdown

Title: Statistical Data Analysis for Randomized Block Design
person(given="Nitesh",family="Shirur Devaraja",email="mail@niteshgpb.in",role = c("aut", "cre")),
Maintainer: Nitesh Shirur Devaraja <mail@niteshgpb.in>
Description: Functions for analysis of bulk data generated from experiments in Randomized block design as per Panse and Sukhatme (1954) <https://books.google.co.in/books?id=Efo9AAAAYAAJ>. Computes analysis of variance; Descriptive statistics parameter like Mean, Minimum, Maximum, CV, Standard error of mean, Standard Error of deviation, CD; Genetic parameter statistics Genotypic Coefficient of Variation, Phenotypic Coefficient of Variation, Heritability in broad sense, Genetic Advance and Genetic Advance per cent mean; Variance and Co-variance matrix of genotypic, phenotypic and environmental; Correlation of genotypic, phenotypic and environmental. Further includes directly publication ready tables.
Imports: utils, stats, lattice, rlist, grid, gridExtra, qpdf
Author: Nitesh Shirur Devaraja [aut, cre],
Aravind J [ctb] (Reference material of augmentedRCBD),

Title: A Predictive Model for Trait Based Community Assembly of Plant
Author: Chaitanya Joshi, Xin Li, Daniel Laughlin
Description: Implements a predictive model of community assembly called 'Traitspace' (Laughlin et al. 2012, Ecology Letters). Traitspace is a hierarchical Bayesian model that translates the theory of trait-based environmental filtering into a statistical model that incorporates intraspecific trait variation to predict the relative abundances and the distributions of species.
The package includes functions to plot the predicted and the observed values. It also includes functions to compare the predicted values against the observed values using a variety of different distance measures and to implement permutation tests to test their statistical significance.
Depends: permute, mclust, graphics, grDevices, stats, utils