Construction of blocked designs with multi block variables

When experimental units are inhomogeneous, blocking the experimental units into categories is crucial so as to estimate the treatment effects precisely. In practice, the inhomogeneity often comes from different sources known as block variables in design terminology. The paper considers the blocking...

Full description

Bibliographic Details
Main Author: Yuna Zhao
Format: Article
Language:English
Published: AIMS Press 2021-04-01
Series:AIMS Mathematics
Subjects:
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2021369?viewType=HTML
id doaj-fbfb66ffb21647e692878068204b2e08
record_format Article
spelling doaj-fbfb66ffb21647e692878068204b2e082021-04-14T01:54:53ZengAIMS PressAIMS Mathematics2473-69882021-04-01666293630810.3934/math.2021369Construction of blocked designs with multi block variablesYuna Zhao0 School of Mathematics and Statistics, Shandong Normal University, Jinan 250358, ChinaWhen experimental units are inhomogeneous, blocking the experimental units into categories is crucial so as to estimate the treatment effects precisely. In practice, the inhomogeneity often comes from different sources known as block variables in design terminology. The paper considers the blocking problems with multi block variables. The construction methods of the optimal blocked regular $ 2^{n-m} $ designs with multi block variables under the general minimum lower order confounding criterion for $ \frac{5N}{16}+1\leq n \leq N-1 $ are provided, where $ N = 2^{n-m} $. https://www.aimspress.com/article/doi/10.3934/math.2021369?viewType=HTMLblocked designfactional factorial designgeneral minimum lower order confoundingmulti block variablesoptimality
collection DOAJ
language English
format Article
sources DOAJ
author Yuna Zhao
spellingShingle Yuna Zhao
Construction of blocked designs with multi block variables
AIMS Mathematics
blocked design
factional factorial design
general minimum lower order confounding
multi block variables
optimality
author_facet Yuna Zhao
author_sort Yuna Zhao
title Construction of blocked designs with multi block variables
title_short Construction of blocked designs with multi block variables
title_full Construction of blocked designs with multi block variables
title_fullStr Construction of blocked designs with multi block variables
title_full_unstemmed Construction of blocked designs with multi block variables
title_sort construction of blocked designs with multi block variables
publisher AIMS Press
series AIMS Mathematics
issn 2473-6988
publishDate 2021-04-01
description When experimental units are inhomogeneous, blocking the experimental units into categories is crucial so as to estimate the treatment effects precisely. In practice, the inhomogeneity often comes from different sources known as block variables in design terminology. The paper considers the blocking problems with multi block variables. The construction methods of the optimal blocked regular $ 2^{n-m} $ designs with multi block variables under the general minimum lower order confounding criterion for $ \frac{5N}{16}+1\leq n \leq N-1 $ are provided, where $ N = 2^{n-m} $.
topic blocked design
factional factorial design
general minimum lower order confounding
multi block variables
optimality
url https://www.aimspress.com/article/doi/10.3934/math.2021369?viewType=HTML
work_keys_str_mv AT yunazhao constructionofblockeddesignswithmultiblockvariables
_version_ 1721527817122873344