The cov.nnve() function implements robust covariance estimation
by the nearest neighbor variance estimation (NNVE) method of
Wang and Raftery (2002) <DOI:10.1198/016214502388618780>.

Computes covariance test for adaptive linear modelling
Richard Lockhart, Jon Taylor, Ryan Tibshirani, Rob Tibshirani
This package computes covariance test for the lasso.

c(person("Ben", "Barnard", email = "ben_barnard@outlook.com", role = c("aut", "cre")),
person("Dean", "Young", email = "dean_young@baylor.edu", role = c("aut")))
Testing functions for Covariance Matrices. These tests include high-dimension homogeneity of covariance
matrix testing described by Schott (2007) <doi:10.1016/j.csda.2007.03.004> and high-dimensional one-sample tests of
covariance matrix structure described by Fisher, et al. (2010) <doi:10.1016/j.jmva.2010.07.004>. Covariance matrix
tests use C++ to speed performance and allow larger data sets.
Ben Barnard [aut, cre],
Dean Young [aut]

Local Polynomial Regression of State Dependent Covariates in
State-Space Models
person(c("Christoffer","Moesgaard"), "Albertsen",
email = "cmoe@aqua.dtu.dk", role = c("aut", "cre"))
Facilitates local polynomial regression for state dependent covariates in state-space models. The functionality can also be used from 'C++' based model builder tools such as 'Rcpp'/'inline', 'TMB', or 'JAGS'.
Christoffer Moesgaard Albertsen [aut, cre]

person(c("Christoffer","Moesgaard"), "Albertsen",
email = "cmoe@aqua.dtu.dk", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-0088-4363"))
Christoffer Moesgaard Albertsen [aut, cre]
(<https://orcid.org/0000-0003-0088-4363>)

Tests on Properties of Space-Time Covariance Functions
c(person("Sandra", "De Iaco", role = c("aut", "cre"),
email = "sandra.deiaco@unisalento.it"),
person("Claudia", "Cappello", role = "aut", email = "claudia.cappello@unisalento.it"),
person("Donato", "Posa", role = "aut", email = "donato.posa@unisalento.it"),
person("Sabrina ", "Maggio", role = "ctb", email = "sabrina.maggio@unisalento.it"))
Tests on properties of space-time covariance functions.
Tests on symmetry, separability and for assessing
different forms of non-separability are available. Moreover tests on
some classes of covariance functions, such that the classes of
product-sum models, Gneiting models and integrated product models have
been provided.
utils, stats, graphics, methods, matrixcalc, gstat, sp (>=
0.9-72), spacetime (>= 1.0-0)
'sepindex.R' 'couples.R' 'blocks.R' 'covablocks.R'
'covastat.R' 'covaprop.R' 'dataprep.R' 'rr_13.R' 'vv_13.R'
Sandra De Iaco [aut, cre],
Claudia Cappello [aut],
Donato Posa [aut],
Sabrina Maggio [ctb]