[PDF] Top 20 Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data
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Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data
... poral model for longitudinal manifold-valued data, which consist in re- peated measurements over time for a group of ...This model allows us to estimate a ... Voir le document complet
13
A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data
... Abstract. Mixed-effects models provide a rich theoretical framework for the analysis of longitudinal ...predict the progression of a neurodegenerative ... Voir le document complet
13
The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.
... of the standard errors (SEs) of the estimated ...parameters. The inverse of the Fisher information matrix provides an upper bound of the estimated variance ... Voir le document complet
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A coherent framework for learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
... as the dimension of the problem. Thus, our observed data consists in a sequence in R kd , y = (y i,j ) (i,j)∈J1,nK×J1,kiK , where J1, nK×J1, k i K denotes for compactness the set ... Voir le document complet
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Methods and algorithms to learn spatio-temporal changes from longitudinal manifold-valued observations
... version of the Expectation-Maximization algorithm, namely the Monte Carlo Markov Chains Stochastic Approximation EM algorithm (MCMC-SAEM), is used to produce produce maximum a posteriori estimates ... Voir le document complet
200
A latent mixed-effects model for longitudinal categorical data in Parkinson disease
... Latent model : we model 𝒚 !" as a Bernoulli realization with parameter 𝜼 !" ∈ ℳ a Riemannian manifold; 𝜼 !" = ℙ 𝒚 !" = 1 is a function of the time describing the ... Voir le document complet
2
Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks
... results Data We used this model to highlight typical spatiotemporal patterns of cortical atro- phy during the course of Alzheimer’s Disease from longitudinal MRI of ... Voir le document complet
9
Analysis of longitudinal neuroimaging data with OLS & Sandwich Estimator of variance
... Statistical analysis of longitudinal neuroimage data with linear mixed effects ...Sabuncu. Spatiotemporal linear mixed effects modeling for the ... Voir le document complet
21
Learning spatiotemporal trajectories from manifold-valued longitudinal data
... framework of mixed-effects models seems to be well suited to deal with this hierarchical prob- ...lem. Mixed-effects models for longitudinal measurements were introduced ... Voir le document complet
10
Learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data
... trajectory of the global pro- gression and together with spacial and temporal inter-individual ...our model in its most generic formulation and then make it explicit for recist [4] score ... Voir le document complet
2
The SwE Toolbox: a Toolbox for the Analysis of Longitudinal and Repeated Measures Neuroimaging Data
... The SwE Toolbox: a Toolbox for the Analysis of Longitudinal and Repeated Measures Neuroimaging Data Bryan Guillaume 1,2 , Xue Hua 3 , Paul ...and the Alzheimer’s ... Voir le document complet
1
Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation
... summarize, for the case study of this small dataset, both models M1 and M2 allow to find Ocimum gratissimum as an alternative plant to Hyptis suaveolens for protecting Arachis hypogaea against ... Voir le document complet
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Criteria for longitudinal data model selection based on Kullback's symmetric divergence
... When the sample size is small or the number of fitted parameters is large to moderate frac- tion of the sample size, both AIC and KIC criteria suffer from a negative bias and result in ... Voir le document complet
15
Instanton calculus for the self-avoiding manifold model
... 3; for details see the discussion in [3, ...are for rather small ...understanding. The theory in question is a generalization of the Edwards model for polymers [10, ... Voir le document complet
120
Criteria for longitudinal data model selection based on Kullback’s symmetric divergence
... to model selection for longitudinal data with correlated ...two model selection criteria: the first one is obtained by applying the maximum likelihood approach and ... Voir le document complet
18
Modelling the influence of data structure on learning in neural networks: the hidden manifold model
... on the projections X and the labels y ∈ R P . The setting of the present paper corresponds to using a committee machine with K hidden units to perform regression on the ... Voir le document complet
44
Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model
... describing the model and the notations (Section 2), Section 3 de- scribes the extended SAEM ...reports the simulation study and its results. We simulate datasets using the ... Voir le document complet
25
Mixed models for longitudinal left-censored repeated measures.
... case of difficulties for convergence, several options are available apart from changing starting points (statement parms) and algorithm (options technique, linesearch, ...update). For example, ... Voir le document complet
19
Towards a model for the multidimensional analysis of field data
... work The term Map Algebra was first introduced in [22] to describe operators on raster data (complete field ...to the number of grids and cells ...to the input grids, cell by cell. ... Voir le document complet
16
Model Assisted Creativity Sessions for the Design of Mixed Interactive Systems: a Protocol Analysis
... Indeed, model transformations are useful tools to infer (parts of) the running proto- type from a source model such as those used in a ...any model. As a result, we could envision ... Voir le document complet
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