About: Quasi-maximum likelihood estimate

Facets (new session)
Description
Metadata
Settings
- Rule:
- Inverse Functional Properties:
- "Same As":

About: Quasi-maximum likelihood estimate Goto Sponge NotDistinct Permalink

An Entity of Type : owl:Thing, within Data Space : dbpedia.demo.openlinksw.com associated with source document(s)
QRcode icon

http://dbpedia.demo.openlinksw.com/describe/?url=http%3A%2F%2Fdbpedia.org%2Fresource%2FQuasi-maximum_likelihood_estimate

In statistics a quasi-maximum likelihood estimate (QMLE), also known as a pseudo-likelihood estimate or a composite likelihood estimate, is an estimate of a parameter θ in a statistical model that is formed by maximizing a function that is related to the logarithm of the likelihood function, but in discussing the consistency and (asymptotic) variance-covariance matrix, we assume some parts of the distribution may be mis-specified. In contrast, the maximum likelihood estimate maximizes the actual log likelihood function for the data and model. The function that is maximized to form a QMLE is often a simplified form of the actual log likelihood function. A common way to form such a simplified function is to use the log-likelihood function of a misspecified model that treats certain data valu

Attributes	Values
rdfs:label	Quasi-maximum likelihood estimate (en)
rdfs:comment	In statistics a quasi-maximum likelihood estimate (QMLE), also known as a pseudo-likelihood estimate or a composite likelihood estimate, is an estimate of a parameter θ in a statistical model that is formed by maximizing a function that is related to the logarithm of the likelihood function, but in discussing the consistency and (asymptotic) variance-covariance matrix, we assume some parts of the distribution may be mis-specified. In contrast, the maximum likelihood estimate maximizes the actual log likelihood function for the data and model. The function that is maximized to form a QMLE is often a simplified form of the actual log likelihood function. A common way to form such a simplified function is to use the log-likelihood function of a misspecified model that treats certain data valu (en)
dcterms:subject	Maximum likelihood estimation
Wikipage page ID	17518635 (xsd:integer)
Wikipage revision ID	1104880266 (xsd:integer)
Link from a Wikipage to another Wikipage	Nuisance parameter Consistent estimator Maximum likelihood estimation Likelihood function Statistical model Normal distribution Parameter Partial likelihood methods for panel data Efficiency (statistics) Maximum likelihood Quasi-likelihood
sameAs	Quasi-maximum likelihood estimate Quasi-maximum likelihood estimate
has abstract	In statistics a quasi-maximum likelihood estimate (QMLE), also known as a pseudo-likelihood estimate or a composite likelihood estimate, is an estimate of a parameter θ in a statistical model that is formed by maximizing a function that is related to the logarithm of the likelihood function, but in discussing the consistency and (asymptotic) variance-covariance matrix, we assume some parts of the distribution may be mis-specified. In contrast, the maximum likelihood estimate maximizes the actual log likelihood function for the data and model. The function that is maximized to form a QMLE is often a simplified form of the actual log likelihood function. A common way to form such a simplified function is to use the log-likelihood function of a misspecified model that treats certain data values as being independent, even when in actuality they may not be. This removes any parameters from the model that are used to characterize these dependencies. Doing this only makes sense if the dependency structure is a nuisance parameter with respect to the goals of the analysis. As long as the quasi-likelihood function that is maximized is not oversimplified, the QMLE (or composite likelihood estimate) is consistent and asymptotically normal. It is less efficient than the maximum likelihood estimate, but may only be slightly less efficient if the quasi-likelihood is constructed so as to minimize the loss of information relative to the actual likelihood. Standard approaches to statistical inference that are used with maximum likelihood estimates, such as the formation of confidence intervals, and statistics for model comparison, can be generalized to the quasi-maximum likelihood setting. (en)
prov:wasDerivedFrom	wikipedia-en:Quasi-maximum_likelihood_estimate?oldid=1104880266&ns=0
page length (characters) of wiki page	3494 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Quasi-maximum_likelihood_estimate
is Link from a Wikipage to another Wikipage of	Quasi-MLE QMLE Quasi-maximum likelihood estimation Christian Gourieroux Quasi-maximum likelihood Partial likelihood methods for panel data Heteroskedasticity-consistent standard errors Quasi-likelihood Composite likelihood Composite likelihood estimate
is Wikipage redirect of	Quasi-MLE QMLE Quasi-maximum likelihood estimation Quasi-maximum likelihood Composite likelihood Composite likelihood estimate
is foaf:primaryTopic of	wikipedia-en:Quasi-maximum_likelihood_estimate

Faceted Search & Find service v1.17_git139 as of Feb 29 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 08.03.3330 as of Mar 19 2024, on Linux (x86_64-generic-linux-glibc212), Single-Server Edition (378 GB total memory, 60 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software