# Best estimators in models with individually split experimental units

Mathematica Applicanda (1982)

- Volume: 10, Issue: 20
- ISSN: 1730-2668

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topHenryk Mikos. "Best estimators in models with individually split experimental units." Mathematica Applicanda 10.20 (1982): null. <http://eudml.org/doc/292745>.

@article{HenrykMikos1982,

abstract = {The author deals with a classical split-plot design in which the effect of levels of factor A, i.e., the whole plot treatments, and the effect of levels of factor B, i.e., the split-plot treatments, on the values of some variable are investigated. He considers four different models: (i) a fixed model, i.e., the effects of both factors are fixed; (ii) two mixed models, i.e., the effects of A are random and the effects of B are fixed, or the effects of A are fixed and the effects of B are random; (iii) a random model, i.e., the effects of both factors are random. It is assumed also that block effects are always random. In all the above linear models, it is proved that, for the estimable functions of the fixed parameters, there exist uniformly best unbiased estimators. Moreover, uniformly best unbiased quadratic estimators of suitable variance components are given in the above linear models. MR0707815},

author = {Henryk Mikos},

journal = {Mathematica Applicanda},

keywords = {Factorial designs, Linear regression, Block designs},

language = {eng},

number = {20},

pages = {null},

title = {Best estimators in models with individually split experimental units},

url = {http://eudml.org/doc/292745},

volume = {10},

year = {1982},

}

TY - JOUR

AU - Henryk Mikos

TI - Best estimators in models with individually split experimental units

JO - Mathematica Applicanda

PY - 1982

VL - 10

IS - 20

SP - null

AB - The author deals with a classical split-plot design in which the effect of levels of factor A, i.e., the whole plot treatments, and the effect of levels of factor B, i.e., the split-plot treatments, on the values of some variable are investigated. He considers four different models: (i) a fixed model, i.e., the effects of both factors are fixed; (ii) two mixed models, i.e., the effects of A are random and the effects of B are fixed, or the effects of A are fixed and the effects of B are random; (iii) a random model, i.e., the effects of both factors are random. It is assumed also that block effects are always random. In all the above linear models, it is proved that, for the estimable functions of the fixed parameters, there exist uniformly best unbiased estimators. Moreover, uniformly best unbiased quadratic estimators of suitable variance components are given in the above linear models. MR0707815

LA - eng

KW - Factorial designs, Linear regression, Block designs

UR - http://eudml.org/doc/292745

ER -

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