Title: Bayesian Semi and Nonparametric Growth Curve Models that
Additionally Include Multiple Membership Random Effects
LinkingTo: Rcpp (>= 0.11.6), RcppArmadillo (>= 0.5.000)

Title: Bayesian non-parametric dependent models for time-indexed
Description: Estimates a collection of time-indexed functions under
either of Gaussian process (GP) or intrinsic Gaussian Markov
random field (iGMRF) prior formulations where a Dirichlet process
mixture allows sub-groupings of the functions to share the same
covariance or precision parameters.  The GP and iGMRF formulations
both support any number of additive covariance or precision terms,
respectively, expressing either or both of multiple trend and
LinkingTo: Rcpp (>= 0.11.2), RcppArmadillo (>= 0.4.000)
Collate: 'MSPE.R' 'cps.R' 'gen_informative_sample.R' 'gpdpgrow.R'

Title: Bayesian Non-Parametric Dependent Models for Time-Indexed

Description: Normal theory repeated measurements models

Title: Multivariate Normal and Elliptically-Contoured Repeated
Description: Functions for fitting various normal theory (growth
curve) and elliptically-contoured repeated measurements models
with ARMA and random effects dependence.

Packaged: 2019-02-04 17:03:32 UTC; swihartbj

Title: Plotting, Smoothing and Growth Trait Extraction for Longitudinal
Imports: dae, ggplot2, stats, XLConnect, Hmisc, GGally, RColorBrewer,
Description: Assists in producing longitudinal or profile plots of measured
traits. These allow checks to be made for anomalous data and growth patterns
in the data to be explored. Smoothing of growth trends for individual plants
using smoothing splines is available for removing transient effects. There
are tools for diagnosing the adequacy of trait smoothing, either using this
package or other packages, such as those that fit nonlinear growth models.
A range of per-unit (pot, plant, plot) growth traits can be extracted from
longitudinal data, including single time-point smoothed trait values and
their growth rates, interval growth rates and other growth statistics, such
as maximum growth. The package is particularly suited to preparing data from
high-throughput phenotyping facilities, such as imaging data from a Lemna-Tec Scananalyzer
information). The package 'growthPheno' can also be installed from