<p>Each observation made by the expert can take one of three category values from . The parameters governing the model are and , where is the true category of the observed data point, and and correspond to the expert labelling the data point as or , respectively.</p
<p>The expert responses are treated as the observed variables and the true image labels as the lat...
Models obtained for each selected variable with Growth Mixture Model analysis.</p
The methodological literature on mixture modeling has rapidly expanded in the past 15 years, and mix...
Mixtures of experts models provide a framework in which covariates may be included in mixture models...
Mixture-of-experts models, or mixture models, are a divide-and-conquer learning method derived from ...
Mixture models are widely used in statistical modeling since they can model situations which a simpl...
It is shown that for finite mixtures the missing information tends to zero as the number of observat...
Finite mixture models are often used to classify two- (units and variables) or three- (units, variab...
Finite mixtures of distributions have provided a mathematical-based approach to the statistical mode...
<p>Each observation made by the expert can take one of three category values from . The parameters...
Posterior mean and 95% credible interval (CI) for the ‘global’ parameters of the mixture model.</p
<div><p>We propose a new class of models providing a powerful unification and extension of existing ...
In this dissertation, we propose several methodology in clustering and mixture modeling when the use...
We investigate the effects of a complex sampling design on the estimation of mixture models. An appr...
<p>Model information of the mixed-effects models used for different diversity components.</p
<p>The expert responses are treated as the observed variables and the true image labels as the lat...
Models obtained for each selected variable with Growth Mixture Model analysis.</p
The methodological literature on mixture modeling has rapidly expanded in the past 15 years, and mix...
Mixtures of experts models provide a framework in which covariates may be included in mixture models...
Mixture-of-experts models, or mixture models, are a divide-and-conquer learning method derived from ...
Mixture models are widely used in statistical modeling since they can model situations which a simpl...
It is shown that for finite mixtures the missing information tends to zero as the number of observat...
Finite mixture models are often used to classify two- (units and variables) or three- (units, variab...
Finite mixtures of distributions have provided a mathematical-based approach to the statistical mode...
<p>Each observation made by the expert can take one of three category values from . The parameters...
Posterior mean and 95% credible interval (CI) for the ‘global’ parameters of the mixture model.</p
<div><p>We propose a new class of models providing a powerful unification and extension of existing ...
In this dissertation, we propose several methodology in clustering and mixture modeling when the use...
We investigate the effects of a complex sampling design on the estimation of mixture models. An appr...
<p>Model information of the mixed-effects models used for different diversity components.</p
<p>The expert responses are treated as the observed variables and the true image labels as the lat...
Models obtained for each selected variable with Growth Mixture Model analysis.</p
The methodological literature on mixture modeling has rapidly expanded in the past 15 years, and mix...