Multivariate Discrete Data Analysis
Multivariate Variance Residual Life in Discrete Time
... In this paper, we have presented several properties of the different versions of multi- variate variance residual life in discrete time. Also the classification of life distributions based on the monotonicity of ...
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Electrocardiogram Beat Classification using Discrete Wavelet Transform, Higher Order Statistics and Multivariate Analysis
... There are three main processes in an ECG arrhythmia detection system, namely, feature extraction, feature selection, and classifier construction. The ECG beat classification [1]as per ANSI/AAMI EC57:1998 standard ...
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Article Visualization of the Strain-rate State of a Data Cloud: Analysis of the Temporal Change of an Urban Multivariate Description
... point-wise data (see, for instance, [33,34]), in this work we apply this well-known method in a three-dimensional ...the discrete approximation F h ( x, t ) ∈ V h of any multi-dimensional ...
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Covariance-based Clustering in Multivariate and Functional Data Analysis
... of multivariate and func- tional ...subdivides data in two groups maximising the distance between their induced ...of discrete covariances of functional data, namely a linear shrinkage ...
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Dynamic staged trees for discrete multivariate time series : forecasting, model selection and causal analysis
... history analysis are local independence graphs (Didelez, 2008) and graphical duration graphs (Gottard, ...history data and the problem outlined here, it is clear that the two address quite separate ...of ...
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Dynamic staged trees for discrete multivariate time series : forecasting, model selection and causal analysis
... further information, a good default is to use the steady model as in the idle system but with a lower value for the steady parameter k. This indicates that past data might not be considered as relevant in helping ...
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Quantitative Trait Linkage Analysis Using Gaussian Copulas
... a multivariate normal ...distributed data, we developed and implemented a modified VC method, which we call the ‘‘copula VC method,’’ that directly models the nonnormal distribution using Gaussian ...the ...
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The Analysis of Bayesian Probit Regression of Binary and Polychotomous Response Data
... the analysis of specific latent data for regression analysis of the discrete data and to build a relation between a probit regression model (related to the discrete response) and ...
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MULTIVARIATE STATISTICAL ANALYSIS OF GROUNDWATER CHEMISTRY DATA FROM HADEJIA LOCAL GOVERNMENT AREA OF JIGAWA STATE, NIGERIA
... The multivariate statistical tools cluster analysis (CA) and principal component analysis (PCA) were simultaneously applied to groundwater hydrochemical data of Hadejia Local Government area ...
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Multivariate analysis of chemical components of tobacco leaves
... the analysis above, it is desirable to conclude that U ˆ 1 of the organic chemical constituents is a “better” representative of its set than U ˆ 1 of the inorganic chemical constituents is of its ...constituents’ ...
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Multivariate analysis of human immunodeficiency virus type 1 neutralization data.
... tion data obtained with peripheral blood mononuclear cells (PBMCs) (15, 25, 30) and primary HIV-1 isolates representing all known genetic clades and both autologous and heterolo- gous HIV-1 sera show that the ...
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Complex sample design effects and inference for mental health survey data
... The complex effects and interactions of stratifica- tion, clustering and estimation weighting that produce design effects in survey estimates are difficult if not impossible to model mathematically. Simple models of ...
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Survival Analysis Part II: Multivariate data analysis - an introduction to concepts and methods
... Several statistical methods have been proposed for modelling survival analysis data. We will describe the most important models and illustrate their application using example datasets described in the ...
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Using a gratitude intervention to enhance wellbeing in older adults
... received an e - mail link to the information sheet, study description, and the researchers' e - mail details for any clarification. Participants were advised that choosing the submit button after reading these was ...
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Spatial and Temporal Distribution of Polychlorinated Biphenyl Residues in Tropical Soils
... pose other organic compounds in the extract since PCBs are not affected by strong acids and oxidizing agents. Clean up with copper granules was to precipitate sulphur in the extract that might interfere with the gas ...
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A brief introduction to multivariate methods in grape and wine analysis
... Many applications require that samples be assigned to pre- defi ned categories, or “classes”. This may involve determining whether a sample is good or bad, or predicting an unknown sample as belonging to one of several ...
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Characterization and Classification of Hydrochemistry using Multivariate Graphical and Hydrostatistical Techniques
... Three multivariate models ...the data matrix classified ...significant data reduction and recognized the most significant marker parameters explaining the variability of water ...programme ...
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In Quest for Improved Drugs against Diabetes: The Added Value of X-ray Powder Diffraction Methods
... of data which are routinely collected from microcrystalline precipitates using synchrotron or laboratory sources [45 - ...XRPD data collection and the uniqueness of the pattern obtained from each polymorph, ...
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Near infrared (NIR) technology and multivariate data analysis for sensing taste attributes of apples
... A Zeiss MMS1 (a fixed Si photo diode array) NIR enhanced spectrometer was used to collect reflectance readings over a wavelength range of 700-1100 nm in 2 nm increments, yielding 200 values per spectrum. For each variety ...
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Influence in time and space of non crop elements with associated functional traits on biocontrol, within the Montepaldi Long Term Experiment, Tuscany
... In this study we evaluated the effects on predation rate (PR) and arthropod abundance (AA) depending on variation in space, production method and time. For this purpose, three a priori defined factors were selected: (1) ...
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