Confidence intervals for point-of-stabilization of content uniformity

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10448839" target="_blank" >RIV/00216208:11320/22:10448839 - isvavai.cz</a>

Result on the web

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ZR~6vsgBd7" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=ZR~6vsgBd7</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/pst.2207" target="_blank" >10.1002/pst.2207</a>

Result language

angličtina

Original language name

Confidence intervals for point-of-stabilization of content uniformity

Original language description

Within the framework of continuous pharmaceutical manufacturing, we are interested in statistical modeling of the initial behavior of the production line. Assuming a gradually changing sequence of a suitable product quality characteristic (e.g., the content uniformity), we estimate the so-called point-of-stabilization (PoSt) and construct corresponding confidence regions based on appropriate asymptotic distributions and bootstrap. We investigate linear, quadratic, and nonlinear gradual change models both in homoscedastic and heteroscedastic setup. We propose a new nonlinear E-max gradual change model and show that it is applicable even if the true model is linear. Asymptotic distribution of the PoSt estimator is known only in a homoscedastic linear and quadratic model and, therefore, bootstrap approximations are used to construct one-sided PoSt confidence intervals.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

<a href="/en/project/GF22-01639K" target="_blank" >GF22-01639K: Gradual Functional Changes - GraFuCha</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Pharmaceutical Statistics

ISSN

1539-1604

e-ISSN

1539-1612

Volume of the periodical

21

Issue of the periodical within the volume

5

Country of publishing house

GB - UNITED KINGDOM

Number of pages

16

Pages from-to

944-959

UT code for WoS article

000773669400001

EID of the result in the Scopus database

2-s2.0-85127341594