general linear model Dotaz Zobrazit nápovědu
Permutation methods are commonly used to test the significance of regressors of interest in general linear models (GLMs) for functional (image) data sets, in particular for neuroimaging applications as they rely on mild assumptions. Permutation inference for GLMs typically consists of three parts: choosing a relevant test statistic, computing pointwise permutation tests, and applying a multiple testing correction. We propose new multiple testing methods as an alternative to the commonly used maximum value of test statistics across the image. The new methods improve power and robustness against inhomogeneity of the test statistic across its domain. The methods rely on sorting the permuted functional test statistics based on pointwise rank measures; still, they can be implemented even for large data. The performance of the methods is demonstrated through a designed simulation experiment and an example of brain imaging data. We developed the R package GET, which can be used for the computation of the proposed procedures.
- MeSH
- lidé MeSH
- lineární modely MeSH
- mozek * diagnostické zobrazování MeSH
- neurozobrazování * MeSH
- počítačová simulace MeSH
- výzkumný projekt MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
V simulační studii (ve výukovém referátu) je po stručném fyziologickém úvodu popsán lineární model izometrické kontrakce kosterního svalu pomocí mechanické analógie. Model se skládá z bloků, z nichž první, generující sílu, představuje kontraktilní aparát a další modelují plastické a elastické vlastnosti svalu na základě pružin a elementů viskozního třeni Platnost modelu je omezena pouze na okolí pracovního bodu činnosti svalu. Výsledky simulace vyjadřují grafy, charakterizující průběh koncentrace vápníkových iontů ve svalu, průběh síly generované svalem a srovnání průběhů této silypři různých periodách budicího signálu. Simulace probíhá v simulačním prostředí MATLAB - SIMULINK, jež tvoří základ výukového simulačního systému, využívaného při výuce předmětu Biokybernetika na katedře kybernetiky FEL, ČVU T v Praze.
After a brief physiological introduction a skeletal nuscle isometric contraction linear model using mezhanical analogy is described in the simulation study. The model consists of blocks; the first of them generaIng force, represents contractile apparatus and the text ones model plastic and elastic muscle qualities on the basis of springs and viscous friction elements. Model validity is limited only on muscle activity working point enviroment The simulation results are presented by graphs characterizing calcium ions in the nuscle concentration course, force generated by muscle course and comparizon of this force courses during various periods of exciting signal The simulation is performed in the MATLAB - SIMULINK environment making the bases of the educational simulation system used by teaching the subject Biocybernetics on the Department of Cybernetics of the Faculty of Electrical Engineering Czech Technical University in Prague.
n3.5.9 Plots with whiskers .40\n\n3.5.10 Curves .41\n\nV\n4 Statistical modelling\n\n4.1 Regression model .43\n\n4.2 General linear model .45\n\n4.3 Generalized linear model .47\n\n4.4 Searching for the “correct ” model 51\n\n4.5 Model selection 53\n\n4.6 Model diagnosis 54\n\n5 The first trial\n\n5.1 An example .61\n\n5.2 EDA 61\n\n5.3 Presumed model .63\n\n5.4 Statistical analysis .63\n\n5.4.1 ANOVA table of 147\n\n9.2 Description of the lognormal model 148\n\n9.3 Regression 149\n\n9.4 Two-way ANODEV 156\n\
First edition x, 245 stran : ilustrace ; 24 cm
- Konspekt
- Biologické vědy
- NLK Obory
- biologie
- statistika, zdravotnická statistika
- knihovnictví, informační věda a muzeologie
- NLK Publikační typ
- kolektivní monografie
Wiley series in probability and statistics
1st ed. xxi, 325 s.
- Konspekt
- Statistika
- NLK Obory
- statistika, zdravotnická statistika
Texts in statistical science
2nd ed. vii, 225 s.
- Konspekt
- Statistika
- NLK Obory
- statistika, zdravotnická statistika
The linear theory of electromigration, including the first-order nonlinear approximation, is generalized to systems with any equilibria fast enough to be considered instantaneous in comparison with the timescale of peak movement. For example, this theory is practically applied in the electrokinetic chromatography (EKC) mode of the CZE. The model enables the calculation of positions and shapes of analyte and system peaks without restricting the number of selectors, the complexation stoichiometry, or simultaneous acid-base equilibria. The latest version of our PeakMaster software, PeakMaster 6-Next Generation, implements the theory in a user-friendly way. It is a free and open-source software that performs all calculations and shows the properties of the background electrolyte and the expected electropherogram within a few seconds. In this paper, we mathematically derive the model, discuss its applicability to EKC systems, and introduce the PeakMaster 6 software.
We discuss several possible phenomena in electrophoretic systems with complexing agents present in the background electrolyte. In our previous work, we extended the linear theory of electromigration with the first-order nonlinear term, which originally applied to acid-base equilibria only, by generalizing it to any fast chemical equilibria. This extension provides us with a fresh insight into the well-established technique of elecktrokinetic chromatography (EKC). We combine mathematical analysis of the generalized model with its solution by means of the new version of our software PeakMaster 6, and experimental data. We re-examine the fundamental equations by Wren and Rowe and Tiselius in the frame of the generalized linear theory of electromigration. Besides, we show that selector concentration can increase inside the interacting-analyte zone due to its complexation with the analyte, which contradicts the generally accepted idea of a consumption of a portion of the selector inside the zone. Next, we focus our discussion on interacting buffers (i.e., buffer constituents that form a complex with the selector). We demonstrate how such side-interaction of the selector with another buffer constituent can influence measuring analyte-selector interactions. Finally, we describe occurrence and mobilities of system peaks in these EKC systems. We investigate systems with fully charged analytes and neutral cyclodextrins as selectors. Although the theory is not limited in terms of the charge and/or the degree of (de)protonation of any constituent, this setup allows us to find analytical solutions to generalized model under approximate, yet realistic, conditions and to demonstrate all important phenomena that may occur in EKC systems. An occurrence of system peaks in a system with fully charged selector is also investigated.
Functional connectivity (FC) analysis is a prominent approach to analyzing fMRI data, especially acquired under the resting state condition. The commonly used linear correlation FC measure bears an implicit assumption of Gaussianity of the dependence structure. If only the marginals, but not all the bivariate distributions are Gaussian, linear correlation consistently underestimates the strength of the dependence. To assess the suitability of linear correlation and the general potential of nonlinear FC measures, we present a framework for testing and estimating the deviation from Gaussianity by means of comparing mutual information in the data and its Gaussianized counterpart. We apply this method to 24 sessions of human resting state fMRI. For each session, matrix of connectivities between 90 anatomical parcel time series is computed using mutual information and compared to results from its multivariate Gaussian surrogate that conserves the correlations but cancels any nonlinearity. While the group-level tests confirmed non-Gaussianity in the FC, the quantitative assessment revealed that the portion of mutual information neglected by linear correlation is relatively minor-on average only about 5% of the mutual information already captured by the linear correlation. The marginality of the non-Gaussianity was confirmed in comparisons using clustering of the parcels-the disagreement between clustering obtained from mutual information and linear correlation was attributable to random error. We conclude that for this type of data, practical relevance of nonlinear methods trying to improve over linear correlation might be limited by the fact that the data are indeed almost Gaussian.
- MeSH
- algoritmy MeSH
- dospělí MeSH
- Fourierova analýza MeSH
- kyslík krev MeSH
- lidé MeSH
- lineární modely MeSH
- magnetická rezonanční tomografie MeSH
- mladý dospělý MeSH
- nervové dráhy fyziologie MeSH
- normální rozdělení MeSH
- odpočinek fyziologie MeSH
- shluková analýza MeSH
- software MeSH
- Check Tag
- dospělí MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Biphasic solvent systems composed of an ionic liquid (IL) and supercritical carbon dioxide (scCO(2)) have become frequented in synthesis, extractions and electrochemistry. In the design of related applications, information on interphase partitioning of the target organics is essential, and the infinite-dilution partition coefficients of the organic solutes in IL-scCO(2) systems can conveniently be obtained by supercritical fluid chromatography. The data base of experimental partition coefficients obtained previously in this laboratory has been employed to test a generalized predictive model for the solute partition coefficients. The model is an amended version of that described before by Hiraga et al. (J. Supercrit. Fluids, in press). Because of difficulty of the problem to be modeled, the model involves several different concepts - linear solvation energy relationships, density-dependent solvent power of scCO(2), regular solution theory, and the Flory-Huggins theory of athermal solutions. The model shows a moderate success in correlating the infinite-dilution solute partition coefficients (K-factors) in individual IL-scCO(2) systems at varying temperature and pressure. However, larger K-factor data sets involving multiple IL-scCO(2) systems appear to be beyond reach of the model, especially when the ILs involved pertain to different cation classes.
