EMMLi: a maximum likelihood approach to the analysis of modularity

A Goswami, JA Finarelli - Evolution, 2016 - academic.oup.com
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …
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EMMLi: A maximum likelihood approach to the analysis of modularity.

A Goswami, JA Finarelli - Evolution; International Journal of Organic …, 2016 - europepmc.org
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …

EMMLi: A maximum likelihood approach to the analysis of modularity

A Goswami, JA Finarelli - Evolution, 2016 - infona.pl
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …

EMMLi: A maximum likelihood approach to the analysis of modularity

A Goswami, JA Finarelli - Evolution, 2016 - Wiley Online Library
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …

EMMLi: A maximum likelihood approach to the analysis of modularity.

A Goswami, JA Finarelli - Evolution, 2016 - search.ebscohost.com
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …

EMMLi: A maximum likelihood approach to the analysis of modularity

A Goswami, JA Finarelli - Evolution; international journal …, 2016 - pubmed.ncbi.nlm.nih.gov
Identification of phenotypic modules, semiautonomous sets of highly correlated traits, can be
accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg, RV …

EMMLi: A maximum likelihood approach to the analysis of modularity

A Goswami, JA Finarelli - Evolution, 2016 - discovery.ucl.ac.uk
Identification of phenotypic modules, semi-autonomous sets of highly-correlated traits, can
be accomplished through exploratory (eg, cluster analysis) or confirmatory approaches (eg …