Constructs shrinkage estimators of high-dimensional mean-variance portfolios and performs
high-dimensional tests on optimality of a given portfolio. The techniques developed in
Bodnar et al. (2018) <doi:10.1016/j.ejor.2017.09.028>, Bodnar et al. (2019)
<doi:10.1109/TSP.2019.2929964>, Bodnar et al. (2020) <doi:10.1109/TSP.2020.3037369>
are central to the package. They provide simple and feasible estimators and tests for optimal
portfolio weights, which are applicable for 'large p and large n' situations where p is the
portfolio dimension (number of stocks) and n is the sample size. The package also includes tools
for constructing portfolios based on shrinkage estimators of the mean vector and covariance matrix
as well as a new Bayesian estimator for the Markowitz efficient frontier recently developed by
Bauder et al. (2021) <doi:10.1080/14697688.2020.1748214>.

Multivariate and Functional Spatial Scan Statistics
c(person("Camille", "FREVENT", role = c("aut", "cre", "cph"), email = "camille.frevent@univ-lille.fr"), person("Mohamed-Salem", "AHMED", role = "aut"), person("Julien", "SOULA", role = "aut"), person("Zaineb", "SMIDA", role = "aut"), person("Lionel", "CUCALA", role = "aut"), person("Sophie", "DABO-NIANG", role = "aut"), person("Michaël", "GENIN", role = "aut"))
Allows to detect spatial clusters of abnormal values on multivariate or functional data. Martin KULLDORFF and Lan HUANG and Kevin KONTY (2009) <doi:10.1186/1476-072X-8-58>, Inkyung JUNG and Ho Jin CHO (2015) <doi:10.1186/s12942-015-0024-6>, Lionel CUCALA and Michael GENIN and Caroline LANIER and Florent OCCELLI (2017) <doi:10.1016/j.spasta.2017.06.001>, Lionel CUCALA and Michael GENIN and Florent OCCELLI and Julien SOULA (2019) <doi:10.1016/j.spasta.2018.10.002>, Zaineb SMIDA and Lionel CUCALA and Ali GANNOUN (2020) <https://hal.archives-ouvertes.fr/hal-02908496>, Camille FREVENT and Mohamed-Salem AHMED and Matthieu MARBAC and Michael GENIN (2021) <arXiv:2011.03482>, Camille FREVENT and Mohamed-Salem AHMED and Sophie DABO-NIANG and Michael GENIN (2021) <arXiv:2103.14401>.
Rcpp, parallel, purrr, matrixStats, SpatialNP, sp, DT,
TeachingDemos, plotrix, fmsb, rgdal, swfscMisc, rgeos
'documentation_page.R' 'clusters.R' 'permutations.R'
'gaussian_multi.R' 'wmw_multi.R' 'wmw_fonc.R' 'scan_fonc.R'
'scan_multi.R' 'plot_map.R''plot_summary.R' 'RcppExports.R'
'dfree_index_multi.R' 'pointwise_dfree.R'
'pointwise_wmw_multi.R' 'pointwise_wmw_uni.R'
'transform_data.R' 'data_fmulti_data.R' 'data_funi_data.R'
'data_multi_data.R' 'data_map_sites.R' 'posteriori_filtering.R'
'non_overlap.R' 'scan_uni.R' 'wmw_uni.R' 'dfree.R'
Camille FREVENT [aut, cre, cph],
Mohamed-Salem AHMED [aut],
Julien SOULA [aut],
Zaineb SMIDA [aut],
Lionel CUCALA [aut],
Sophie DABO-NIANG [aut],
Michaël GENIN [aut]