Pages that link to "Item:Q583773"

The following pages link to A maximum likelihood methodology for clusterwise linear regression (Q583773):

Displaying 30 items.

• Statistical and machine learning approaches for the minimization of trigger errors in parametric earthquake catastrophe bonds (Q4606120) (← links)
• Prediction for regularized clusterwise multiblock regression (Q4627104) (← links)
• Nonsmooth DC programming approach to clusterwise linear regression: optimality conditions and algorithms (Q4638918) (← links)
• Flexible mixture modelling with the polynomial Gaussian cluster-weighted model (Q4970990) (← links)
• A new look at the inverse Gaussian distribution with applications to insurance and economic data (Q5036583) (← links)
• A new model selection procedure for finite mixture regression models (Q5077504) (← links)
• Estimation and variable selection for mixture of joint mean and variance models (Q5079196) (← links)
• (Q5093363) (← links)
• Penalized estimation in finite mixture of ultra-high dimensional regression models (Q5095987) (← links)
• Model-based clustering via skewed matrix-variate cluster-weighted models (Q5096675) (← links)
• Multivariate linear regression for heterogeneous data (Q5129008) (← links)
• Random effects regression mixtures for analyzing infant habituation (Q5130258) (← links)
• Unsupervised learning of regression mixture models with unknown number of components (Q5222481) (← links)
• Finite Mixture of Linear Regression Models: An Adaptive Constrained Approach to Maximum Likelihood Estimation (Q5348623) (← links)
• Algorithms for Generalized Clusterwise Linear Regression (Q5364278) (← links)
• The role of optimization in some recent advances in data-driven decision-making (Q6044973) (← links)
• Spatial clustering of time series via mixture of autoregressions models and Markov random fields (Q6064123) (← links)
• A unified framework for bivariate clustering and regression problems via mixed-integer linear programming (Q6103471) (← links)
• Clusterwise elastic-net regression based on a combined information criterion (Q6106146) (← links)
• Robust mixture regression modeling based on two-piece scale mixtures of normal distributions (Q6106157) (← links)
• Seemingly unrelated clusterwise linear regression for contaminated data (Q6157046) (← links)
• Leveraging Weather Dynamics in Insurance Claims Triage Using Deep Learning (Q6567876) (← links)
• A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions (Q6581653) (← links)
• Mixture of experts distributional regression: implementation using robust estimation with adaptive first-order methods (Q6589380) (← links)
• A mixture of experts regression model for functional response with functional covariates (Q6606949) (← links)
• Extending finite mixtures of nonlinear mixed-effects models with covariate-dependent mixing weights (Q6613887) (← links)
• Trajectory clustering using mixed classification models (Q6628123) (← links)
• Generalized finite mixture of multivariate regressions with applications to therapeutic biomarker identification (Q6629898) (← links)
• Performance characterization of clusterwise linear regression algorithms (Q6642759) (← links)
• An effective method for identifying clusters of robot strengths (Q6661267) (← links)