R (>= 3.2),fields, wavethresh, xts, zoo,methods

Imputation Methods for Multivariate Locally Stationary Time
Series
Rebecca Wilson [aut],
Matt Nunes [aut, cre],
Idris Eckley [ctb, ths],
Tim Park [ctb]
c(person("Rebecca", "Wilson", role = "aut"), person("Matt", "Nunes", role=c("aut","cre"), email="nunesrpackages@gmail.com"), person("Idris", "Eckley", role=c("ctb","ths")), person("Tim","Park", role="ctb"))
Implementation of imputation techniques based on locally stationary wavelet time series forecasting methods from Wilson, R. E. et al. (2021) <doi:10.1007/s11222-021-09998-2>.

A General Framework of Multivariate Mixed-Effects Selection
Models
Offers a general framework of multivariate mixed-effects
models for the joint analysis of multiple correlated outcomes with clustered
data structures and potential missingness proposed by Wang et al. (2018) <doi:10.1093/biostatistics/kxy022>. The missingness of outcome values may
depend on the values themselves (missing not at random and non-ignorable),
or may depend on only the covariates (missing at random and ignorable), or both.
This package provides functions for two models: 1) mvMISE_b()
allows correlated outcome-specific random intercepts with a factor-analytic
structure, and 2) mvMISE_e() allows the correlated outcome-specific
error terms with a graphical lasso penalty on the error precision matrix. Both functions
are motivated by the multivariate data analysis on data with clustered structures
from labelling-based quantitative proteomic studies. These models and functions
can also be applied to univariate and multivariate analyses of clustered data
with balanced or unbalanced design and no missingness.

Multivariate Comparative Tools for Fitting Evolutionary Models
to Morphometric Data
Julien Clavel, with contributions from Aaron King, and Emmanuel Paradis
Fits multivariate (Brownian Motion, Early Burst, ACDC, Ornstein-Uhlenbeck and Shifts) models of continuous traits evolution on trees
R(>= 2.9.1), phytools, ape, corpcor, subplex

Fits multivariate (Brownian Motion, Early Burst, ACDC, Ornstein-Uhlenbeck and Shifts) models of continuous traits evolution on trees.
R(>= 2.9.1), phytools, ape, corpcor, subplex, spam