Changing Parameters by Partial Mappings
Artikel i vetenskaplig tidskrift, 2010

Changes between different sets of parameters are often needed in multivariate statistical modeling, such as transformations within linear regression or in exponential models. There may, for instance, be specific inference questions based on subject matter interpretations, alternative well-fitting constrained models, compatibility judgements of seemingly distinct constrained models, or different reference priors under alternative parameterizations. We introduce and discuss a partial mapping, called partial replication, and relate it to a more complex mapping, called partial inversion. Both operations are used to decompose matrix operations, to explain recursion relations among sets of linear parameters, to change between different types of linear models, to approximate maximum-likelihood estimates in exponential family models under independence constraints, and to switch partially between sets of canonical and moment parameters in exponential family distributions or between sets of corresponding maximum-likelihood estimates.

TESTS

INDEPENDENCE

SYSTEMS

VARIABLES

MODELS

partial replication

REML-estimates

matrix operators

inversion

GRAPHS

partial

DISCRETE

reduced model estimates

LIKELIHOOD

Exponential family

sandwich estimates

independence constraints

SEEMINGLY UNRELATED REGRESSIONS

Författare

M. Wiedenbeck

Nanny Wermuth

Chalmers, Matematiska vetenskaper, matematisk statistik

Göteborgs universitet

Statistica Sinica

1017-0405 (ISSN)

Vol. 20 823-836

Ämneskategorier

Sannolikhetsteori och statistik