Pages that link to "Item:Q434890"
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The following pages link to Initializing the EM algorithm in Gaussian mixture models with an unknown number of components (Q434890):
Displaying 39 items.
- Manly transformation in finite mixture modeling (Q158374) (← links)
- Using mixtures in seemingly unrelated linear regression models with non-normal errors (Q340854) (← links)
- A robust EM clustering algorithm for Gaussian mixture models (Q437776) (← links)
- Using conditional independence for parsimonious model-based Gaussian clustering (Q746302) (← links)
- Flexible mixture modelling using the multivariate skew-\(t\)-normal distribution (Q892802) (← links)
- Extending mixtures of factor models using the restricted multivariate skew-normal distribution (Q900823) (← links)
- Choosing starting values for the EM algorithm for getting the highest likelihood in multivariate Gaussian mixture models (Q951824) (← links)
- Cox proportional hazards models with frailty for negatively correlated employment processes (Q1615240) (← links)
- Model-based clustering of high-dimensional data: a review (Q1621282) (← links)
- A multivariate linear regression analysis using finite mixtures of \(t\) distributions (Q1621290) (← links)
- Asymmetric clusters and outliers: mixtures of multivariate contaminated shifted asymmetric Laplace distributions (Q1727862) (← links)
- An extension of the \(K\)-means algorithm to clustering skewed data (Q1729355) (← links)
- Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method (Q1784562) (← links)
- Adaptive fault detection and diagnosis using parsimonious Gaussian mixture models trained with distributed computing techniques (Q1796632) (← links)
- A greedy EM algorithm for Gaussian mixture learning (Q1857734) (← links)
- Computational aspects of fitting mixture models via the expectation-maximization algorithm (Q1927163) (← links)
- Mixtures of factor analyzers with covariates for modeling multiply censored dependent variables (Q2062372) (← links)
- Randomly initialized EM algorithm for two-component Gaussian mixture achieves near optimality in \(O(\sqrt{n})\) iterations (Q2113265) (← links)
- Estimation of finite mixture models of skew-symmetric circular distributions (Q2202039) (← links)
- Bayesian approach for mixture models with grouped data (Q2259772) (← links)
- An effective strategy for initializing the EM algorithm in finite mixture models (Q2418282) (← links)
- Improved initialisation of model-based clustering using Gaussian hierarchical partitions (Q2418409) (← links)
- Finite mixture modeling of Gaussian regression time series with application to dendrochronology (Q2628066) (← links)
- Studying Complexity of Model-based Clustering (Q2816737) (← links)
- A Gaussian mixture model based \(k\)-means to initialize the EM algorithm (Q2858834) (← links)
- (Q4546646) (← links)
- Initializing the EM Algorithm for Univariate Gaussian, Multi-Component, Heteroscedastic Mixture Models by Dynamic Programming Partitions (Q4563129) (← links)
- EXPECTED MAXIMIZATION ALGORITHM: PROJECTION DEPTH APPROACH (Q5033479) (← links)
- Practical Initialization of Recursive Mixture-Based Clustering for Non-negative Data (Q5053648) (← links)
- Multiscale Gaussian convolution algorithm for estimate of Gaussian mixture model (Q5077951) (← links)
- EM Estimation for Finite Mixture Models with Known Mixture Component Size (Q5265812) (← links)
- EM for mixtures (Q5963775) (← links)
- Parsimonious mixtures for the analysis of tensor-variate data (Q6063148) (← links)
- Initialization of Hidden Markov and Semi‐Markov Models: A Critical Evaluation of Several Strategies (Q6088634) (← links)
- Parameter identification for Wiener-finite impulse response system with output data of missing completely at random mechanism and time delay (Q6493673) (← links)
- Challenges in model-based clustering (Q6562689) (← links)
- Matrix-variate normal mean-variance Birnbaum-Saunders distributions and related mixture models (Q6567402) (← links)
- Recent developments in expectation-maximization methods for analyzing complex data (Q6607911) (← links)
- On the use of the matrix-variate tail-inflated normal distribution for parsimonious mixture modeling (Q6614843) (← links)
