Estimation of Subject-Specific Heritabilities From Intra-Individual Variation: iFACE

2012 ◽  
Vol 15 (3) ◽  
pp. 393-400 ◽  
Author(s):  
Peter C. M. Molenaar ◽  
Dirk J. A. Smit ◽  
Dorret I. Boomsma ◽  
John R. Nesselroade
Keyword(s):  
Genetic Factor ◽  
Factor Model ◽  
Parametric Model ◽  
Specific Model ◽  
Model Parameters ◽  
Dizygotic Twin ◽  
Subject Specificity ◽  
Subject Specific ◽  
Genetic And Environmental Factors ◽  
Psychophysiological Data

A new genetic factor model for multivariate phenotypic time series, iFACE, is presented which allows for the estimation of subject-specific model parameters of genetic and environmental factors. The iFACE was applied to multivariate EEG registrations obtained with single dizygotic twin pairs. The results showed evidence for considerable subject-specificity in heritabilities and environmental effects. The assumption that the population is homogeneous (i.e., that each case in the population obeys the same parametric model), does not hold for these psychophysiological data, and its use should be critically reconsidered. We conclude that the iFACE provides a powerful new methodology to assess heterogeneity (subject-specificity) based on phenotypic observations.

scholarly journals Determination of subject-specific model parameters for visco-elastic elements

2006 ◽  
Vol 39 (10) ◽  
pp. 1883-1890 ◽  
Author(s):  
Cassie Wilson ◽  
Mark A. King ◽  
Maurice R. Yeadon
Keyword(s):  
Specific Model ◽  
Model Parameters ◽  
Subject Specific ◽  
Elastic Elements

Estimating the actual subject-specific genetic correlations in behavior genetics

2012 ◽  
Vol 35 (5) ◽  
pp. 373-374 ◽  
Author(s):  
Peter C. M. Molenaar
Keyword(s):  
State Space ◽  
Phenotypic Variation ◽  
Genetic Factor ◽  
Behavior Genetics ◽  
Factor Model ◽  
State Space Model ◽  
Genetic Correlations ◽  
Intraindividual Variation ◽  
Space Model ◽  
Subject Specific

AbstractGeneralization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

Measurement Invariance of Divergent Thinking Across Gender, Age, and School Forms

2009 ◽  
Vol 25 (1) ◽  
pp. 1-7 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Heinz Holling
Keyword(s):  
Measurement Invariance ◽  
Divergent Thinking ◽  
Factor Model ◽  
Age Groups ◽  
Thinking Skills ◽  
Specific Model ◽  
Confirmatory Factor Analyses ◽  
Domain Specific ◽  
Gender And Age ◽  
Confirmatory Factor

The present study explores the factorial structure and the degree of measurement invariance of 12 divergent thinking tests. In a large sample of German students (N = 1328), a three-factor model representing verbal, figural, and numerical divergent thinking was supported. Multigroup confirmatory factor analyses revealed that partial strong measurement invariance was tenable across gender and age groups as well as school forms. Latent mean comparisons resulted in significantly higher divergent thinking skills for females and students in schools with higher mean IQ. Older students exhibited higher latent means on the verbal and figural factor, but not on the numerical factor. These results suggest that a domain-specific model of divergent thinking may be assumed, although further research is needed to elucidate the sources that negatively affect measurement invariance.

scholarly journals Determination of exothermic batch reactor specific model parameters

2019 ◽  
Vol 292 ◽  
pp. 01063
Author(s):  
Lubomír Macků
Keyword(s):  
Rate Constant ◽  
Reaction Rate ◽  
Batch Reactor ◽  
Specific Model ◽  
Reaction Rate Constant ◽  
Order Reaction ◽  
First Order Reaction ◽  
Model Parameters ◽  
Reactor Model ◽  
First Order

An alternative method of determining exothermic reactor model parameters which include first order reaction rate constant is described in this paper. The method is based on known in reactor temperature development and is suitable for processes with changing quality of input substances. This method allows us to evaluate the reaction substances composition change and is also capable of the reaction rate constant (parameters of the Arrhenius equation) determination. Method can be used in exothermic batch or semi- batch reactors running processes based on the first order reaction. An example of such process is given here and the problem is shown on its mathematical model with the help of simulations.

Markerless Motion Capture through Visual Hull, Articulated ICP and Subject Specific Model Generation

2009 ◽  
Vol 87 (1-2) ◽  
pp. 156-169 ◽  
Author(s):  
Stefano Corazza ◽  
Lars Mündermann ◽  
Emiliano Gambaretto ◽  
Giancarlo Ferrigno ◽  
Thomas P. Andriacchi
Keyword(s):  
Motion Capture ◽  
Specific Model ◽  
Model Generation ◽  
Visual Hull ◽  
Markerless Motion Capture ◽  
Subject Specific

scholarly journals Inflationary cosmology in unimodular F(T) gravity

2017 ◽  
Vol 32 (21) ◽  
pp. 1750114 ◽  
Author(s):  
Kazuharu Bamba ◽  
Sergei D. Odintsov ◽  
Emmanuel N. Saridakis
Keyword(s):  
Spectral Index ◽  
Teleparallel Gravity ◽  
Specific Model ◽  
Inflationary Cosmology ◽  
Model Parameters ◽  
De Sitter ◽  
Reconstruction Procedure ◽  
Additional Advantage ◽  
Slow Roll ◽  
Good Agreement

We investigate the inflationary realization in the context of unimodular F(T) gravity, which is based on the F(T) modification of teleparallel gravity, in which one imposes the unimodular condition through the use of Lagrange multipliers. We develop the general reconstruction procedure of the F(T) form that can give rise to a given scale-factor evolution, and then we apply it in the inflationary regime. We extract the Hubble slow-roll parameters that allow us to calculate various inflation-related observables, such as the scalar spectral index and its running, the tensor-to-scalar ratio, and the tensor spectral index. Then, we examine the particular cases of de Sitter and power-law inflation, of Starobinsky inflation, as well as inflation in a specific model of unimodular F(T) gravity. As we show, in all cases the predictions of our scenarios are in a very good agreement with Planck observational data. Finally, inflation in unimodular F(T) gravity has the additional advantage that it always allows for a graceful exit for specific regions of the model parameters.

Unknown Parameter Excitation and Estimation for Complex Systems With Dynamic Performances

2021 ◽  
Vol 143 (9) ◽  
Author(s):  
Yi-Ping Chen ◽  
Kuei-Yuan Chan
Keyword(s):  
Complex Systems ◽  
Simulation Models ◽  
Credible Interval ◽  
Specific Model ◽  
Model Parameters ◽  
Real Model ◽  
Dynamic Case ◽  
Dynamic Performances ◽  
Validation Stage ◽  
Setting Parameters

Abstract Simulation models play crucial roles in efficient product development cycles, therefore many studies aim to improve the confidence of a model during the validation stage. In this research, we proposed a dynamic model validation to provide accurate parameter settings for minimal output errors between simulation models and real model experiments. The optimal operations for setting parameters are developed to maximize the effects by specific model parameters while minimizing interactions. To manage the excessive costs associated with simulations of complex systems, we propose a procedure with three main features: the optimal excitation based on global sensitivity analysis (GSA) is done via metamodel techniques, for estimating parameters with the polynomial chaos-based Kalman filter, and validating the updated model based on hypothesis testing. An illustrative mathematical model was used to demonstrate the detail processes in our proposed method. We also apply our method on a vehicle dynamic case with a composite maneuver for exciting unknown model parameters such as inertial and coefficients of the tire model; the unknown model parameters were successfully estimated within a 95% credible interval. The contributions of this research are also underscored through multiple cases.

Cluster Analysis of Dynamic Parameters of Gene Expression

2003 ◽  
Vol 01 (03) ◽  
pp. 447-458 ◽  
Author(s):  
Xiwei Wu ◽  
T. Gregory Dewey
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Cluster Analysis ◽  
Hierarchical Cluster ◽  
Specific Model ◽  
Model Parameters ◽  
Dynamic Parameters ◽  
Clustering Methods ◽  
Transition Matrices ◽  
Great Utility

Cluster analysis has proven to be a valuable statistical method for analyzing whole genome expression data. Although clustering methods have great utility, they do represent a lower level statistical analysis that is not directly tied to a specific model. To extend such methods and to allow for more sophisticated lines of inference, we use cluster analysis in conjunction with a specific model of gene expression dynamics. This model provides phenomenological dynamic parameters on both linear and non-linear responses of the system. This analysis determines the parameters of two different transition matrices (linear and nonlinear) that describe the influence of one gene expression level on another. Using yeast cell cycle microarray data as test set, we calculated the transition matrices and used these dynamic parameters as a metric for cluster analysis. Hierarchical cluster analysis of this transition matrix reveals how a set of genes influence the expression of other genes activated during different cell cycle phases. Most strikingly, genes in different stages of cell cycle preferentially activate or inactivate genes in other stages of cell cycle, and this relationship can be readily visualized in a two-way clustering image. The observation is prior to any knowledge of the chronological characteristics of the cell cycle process. This method shows the utility of using model parameters as a metric in cluster analysis.

scholarly journals LWD DATA INVERSION FOR STRUCTURE WITH ANGULAR UNCONFORMITY

2021 ◽  
Vol 2 (1) ◽  
pp. 336-344
Author(s):  
Anna S. Astrakova ◽  
Elena V. Konobriy ◽  
Dmitry Yu. Kushnir ◽  
Nikolay N. Velker ◽  
Gleb V. Dyatlov
Keyword(s):  
Real Time ◽  
Optimization Method ◽  
Parametric Model ◽  
Model Parameters ◽  
Time Inversion ◽  
Water Contact ◽  
2D Inversion ◽  
Angular Unconformity ◽  
Oil Water ◽  
2D Resistivity

Non-structural traps and reservoir flanks are characterized by angular unconformities. Angular unconformity between dipping formation and sub-horizontal oil-water contact is common in the North Sea fields. This paper presents an approach to real-time inversion of LWD resistivity data for the scenario with angular unconformity. The approach utilizes artificial neural networks (ANNs) for calculating the tool responses in parametric surface-based 2D resistivity models. We propose a parametric model with two non-parallel boundaries suitable for scenarios with angular unconformity and pinch-out. Training of ANNs for this parametric model is performed using a database containing samples with the model parameters and corresponding tool responses. ANNs are the kernel of 2D inversion based on the Levenberg-Marquardt optimization method. To demonstrate applicability of our approach and compare with the results of 1D inversion, we analyze Extra Deep Azimuthal Resistivity tool responses in a 2D synthetic model. It is shown that 1D inversion determines either the position of the oil-water contact or dipping layers structure. At the same time, 2D inversion makes it possible to correctly reconstruct the positions of non-parallel boundaries. Performance of 2D inversion based on ANNs is suitable for real-time applications.

scholarly journals Regression Analysis of the Left-ventricular Isochoric Pressure Decay of the Heart: Four or Five Model Parameters?

2015 ◽  
Vol 4 ◽  
pp. 53
Author(s):  
John Langer
Keyword(s):  
Guinea Pig ◽  
Kinematic Model ◽  
Parametric Model ◽  
Left Ventricular ◽  
Model Parameters ◽  
Decay Data ◽  
Pressure Decay ◽  
Rat Hearts ◽  
Regression Error ◽  
Damped Oscillation

BACKGROUND: Isochoric (isovolumic) cardiac pressure decay data were previously described by a four-parametric logistic (tangens hyperbolicus) regression model (Langer model). However, a five-parametric kinematic model (Chung model), according to the differential equation of damped oscillation, was recently introduced to describe the isochoric pressure fall. The present study clarifies (a/) whether these five parameters can be reliably estimated from empirical pressure decay data and if the model excels the four-parametric one, and (b/) whether the kinematic Chung model validly describes these pressure decays. METHODS: High-fidelity intraventricular pressure decay data from 1203 isolated working guinea pig and rat hearts were analyzed by both models. RESULTS: Most cases present with a higher regression error in the five-parametric kinematic model, the median ratio (F value) of its regression variance by those of the four-parametric logistic model is 1.004 (95 per cent confidence interval: 1.002 to 1.006) in in the guinea pig as well as in the rat group. Additionally, the parameters of both models were estimated from the first and second half of the decay phase separately to check for the models' validity.  The five-parametric model yields significantly non-constant parameters more often than the four-parametric model. CONCLUSION: (a) the five parameters of the kinematic Chung model remain underdetermined by the empirical pressure data, and {b) this five-parametric model does not provide a valid description of the isochoric cardiac pressure decay.

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