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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper we provide a comprehensive study of statistical inference inlinear and allied models which exhibit some analytic perturbations in theirdesign and covariance matrices. We also indicate a few potential applications.In the theory of perturbations of linear operators it has been known for a longtime that the so-called ``singular perturbations'' can have a big impact onsolutions of equations involving these operators even when their size is small.It appears that so far the question of whether such undesirable phenomena canalso occur in statistical models and their solutions has not been formallystudied. The models considered in this article arise in the context ofnonlinear models where a single parameter accounts for the nonlinearity.

Analytic perturbations and systematic bias in statistical modeling and inference