English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Numerical nonlinear algebra is applied to maximum likelihood estimation forGaussian models defined by linear constraints on the covariance matrix. Weexamine the generic case as well as special models (e.g. Toeplitz, sparse,trees) that are of interest in statistics. We study the maximum likelihooddegree and its dual analogue, and we introduce a new software packageLinearCovarianceModels.jl for solving the score equations. All local maxima canthus be computed reliably. In addition we identify several scenarios for whichthe estimator is a rational function.

Estimating linear covariance models with numerical nonlinear algebra