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[PDF] Top 20 A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data

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A mixed-effects model with time reparametrization for longitudinal univariate manifold-valued data

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 ...of a neurodegenerative disease such as Alzheimer’s disease, these models ... Voir le document complet

13

Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data

Mixed-effects model for the spatiotemporal analysis of longitudinal manifold-valued data

... on a man- ifold. The random effects of the model allow to spatially and temporally register individual trajectories of ...spatiotemporal model belongs to a class of statistical models ... Voir le document complet

13

A latent mixed-effects model for longitudinal categorical data in Parkinson disease

A latent mixed-effects model for longitudinal categorical data in Parkinson disease

... from manifold-valued longitudinal ...S. A Bayesian mixed-effects model to learn trajectories of changes from repeated manifold-valued ... Voir le document complet

2

Mixed models for longitudinal left-censored repeated measures.

Mixed models for longitudinal left-censored repeated measures.

... used with NLMIXED through the option technique such as Conjugate Gradient, Double Dogleg, Nelder-Mead Simplex, classic, Ridge or Quasi ...performs a Quasi-Newton optimisation. This algorithm works ... Voir le document complet

19

Varying-Time Random Effects Models for Longitudinal Data: Spatial Disaggregation and Temporal Interpolation of Remote Sensing Data

Varying-Time Random Effects Models for Longitudinal Data: Spatial Disaggregation and Temporal Interpolation of Remote Sensing Data

... nonlinear mixed effects models are nowadays still not efficient enough to cope with such large data sets (see ...at a local scale of quantities such as soil moisture combined ... Voir le document complet

29

Phenomenological modeling of tumor diameter growth based on a mixed effects model

Phenomenological modeling of tumor diameter growth based on a mixed effects model

... oped for the phenomenological modeling of tumor ...propose a new tumor diameter growth function composed of two linear parts and one ex- ponential term to characterize early, late and steady-state treatment ... Voir le document complet

30

The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.

The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.

... models with missing or non-observed data such as random effects is the Expectation-Maximization (EM) algorithm ...the model, stochastic versions of the EM algorithm are ...algorithms, ... Voir le document complet

30

Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

Statistical learning of spatiotemporal patterns from longitudinal manifold-valued networks

... the model subject to important ...consistent with previous knowledge of the Alzheimer’s Disease effects on the brain ...the model is able to exhibit individual spatiotemporal patterns ... Voir le document complet

9

A coherent framework for learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data

A coherent framework for learning spatiotemporal piecewise-geodesic trajectories from longitudinal manifold-valued data

... linked with the intrinsic geometry of observed shapes, from temporal deformations, related to acquisition constraints, is a mean of freeing oneself from this ...estimate a continuous trajectory of ... Voir le document complet

40

Methods and algorithms to learn spatio-temporal changes from longitudinal manifold-valued observations

Methods and algorithms to learn spatio-temporal changes from longitudinal manifold-valued observations

... Appendices A A review of mixed-eects models and their limita- tions in the context of manifold-valued data Remarkable developments have been made in the past 30 years regarding ... Voir le document complet

200

Learning spatiotemporal trajectories from manifold-valued longitudinal data

Learning spatiotemporal trajectories from manifold-valued longitudinal data

... propose a generic statistical framework for the definition and estimation of mixed- effects models for longitudinal manifold-valued ...derive a method that ... Voir le document complet

10

Learning spatio-temporal trajectories from manifold-valued longitudinal data

Learning spatio-temporal trajectories from manifold-valued longitudinal data

... item). Data collected from the ADNI database for 248 MCI patients who converted to ...is a point in 𝑀 = ]0,1[ 4 . Left : the plot of individual random effects show that the time-shifts ... Voir le document complet

2

The Value of a Statistical Life: A Meta-Analysis with a Mixed Effects Regression Model

The Value of a Statistical Life: A Meta-Analysis with a Mixed Effects Regression Model

... accept a certain amount to see his life expectancy ...of a completely anonymous member of ...of a statistical life” (VSL). We shall at no time touch on any of the sentimental and ethical ... Voir le document complet

60

Criteria for longitudinal data model selection based on Kullback's symmetric divergence

Criteria for longitudinal data model selection based on Kullback's symmetric divergence

... Longitudinal data analysis has been a great deal of interest in the fields of clinical tri- als, epidemiology, agriculture and medicine over the last ...These data arise when repeated ... Voir le document complet

15

Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation

Effects of Input Data Formalisation in Relational Concept Analysis for a Data Model with a Ternary Relation

... appropriate for the dataset on both M1 and M2 original ...on a real question raised by the ...lattice. A concept which appears in the concept lattice and not in the AOC-poset represents a ... Voir le document complet

18

A test for a new modelling : The Univariate MT-STAR Model

A test for a new modelling : The Univariate MT-STAR Model

... properties for all values of T . 6. Empirical Illustration We now propose a real exercise to compare the accuracy of our proposed tests on real ...become a very popular tool in the literature that is ... Voir le document complet

36

Criteria for longitudinal data model selection based on Kullback’s symmetric divergence

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 the second is ... Voir le document complet

18

SLIDER: Software for LongItudinal Data Exploration with R

SLIDER: Software for LongItudinal Data Exploration with R

... analyze longitudinal data, presenting step by step four graphical displays implemented in the well-known TraMineR R package (Gabadinho et ...plot for sequence ...is a new graphical display ... Voir le document complet

11

A data model for supplying a Data Center with several energy sources

A data model for supplying a Data Center with several energy sources

... approach with RenewSim is to feed a Data Center with renewable energy in a smart way, thanks to a control ...of a center of calculation in an electrical net- work powered ... Voir le document complet

7

A BIVARIATE FAILURE TIME MODEL, WITH DEPENDENCE DUE TO SHOCKS AND MIXED EFFECT

A BIVARIATE FAILURE TIME MODEL, WITH DEPENDENCE DUE TO SHOCKS AND MIXED EFFECT

... by a non fatal shock of a random amount, with possible dependence between the simultaneous increments of the two failure ...formula for the joint distribution of the bivariate lifetime of the ... Voir le document complet

9

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