General statistics, univariate, and multivariate analyses
Effects of wheat cultivar and harvest year on technological quality studied by univariate and multivariate analyses
... Bread volumes of the cultivar Bezostaja are in correspondence with the protein contents in each harvest year, but bread volumes from the cultivar Jagger were mutually comparable rega[r] ...
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P< 0.001). Univariate and multivariate survival analyses further showed that miR-182 expression was
... and multivariate analyses of prog- nostic variables in CRC patients To determine whether expression of miR-182 is an independent prognostic factor for CRC, uni- variate and multivariate ...
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Multivariate analyses
... Partitioning multivariate variance Reporting multivariate outcome When we have run the MANOVA analysis in SPSS, we are presented with several lines of multivar- iate ...
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Univariate and multivariate Pareto models
... for multivariate Pareto data. Creative Bayesian analyses involving informative priors, in multivariate settings and in cases involving covariates, are also notable for their ...
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MetaPhat : Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics
... by multivariate tests, which have become more practical through recent implementations that require only univariate summary statistics, such as MultiPhen ( O’Reilly et ...summary statistics ...
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Bias in Estimating Multivariate and Univariate Diffusions
... Abstract Multivariate continuous time models are now widely used in economics and ...linear multivariate continuous time systems that includes the commonly used Euler and trapezoidal approximations as ...
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A Univariate, Bivariate and Multivariate Extensions for the Inverse Rayleigh Model with Properties and Applications to the Univariate Version
... new univariate extension of the Inverse Rayleigh distribution is proposed and ...order statistics, quantile spread ordering, Rényi, Shannon and q-entropies are ...and multivariate extensions of the ...
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Shapelet Transforms for Univariate and Multivariate Time Series Classification
... scale analyses of multivariate datasets, where most studies had focused on a handful of ...decisive multivariate shapelet transform that outperformed all other approaches, however, this was not the ...
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On the Univariate Representation of Multivariate Volatility Models with Common Factors
... some multivariate models accounting for co-movements and show that the implied marginal volatility processes are of low ...a general multivariate framework, with correlated conditional variances and ...
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Essays on univariate and multivariate modeling of financial market risks
... workload. Time-series data for the four assets are retrieved from Thomson Reuters Financial Datastream. To account for known data errors in Datastream, we follow Ince and Porter (2006) and apply the following data ...
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Univariate and multivariate ARIMA versus vector autoregression forecasting
... f o r e c a s t s . These models d i f f e r i n how t h e y model t h e r e l a t i o n s h i p s among t h e s e r i e s . Both VAR and BVAR assume t h a t t h e r e l a t i o n s h i p s can be approximated by u s i n ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... of univariate bias- adjustment methods for multivariate ...our analyses are of a rather conceptual na- ture and thus also apply to other climate model outputs, for instance from regional climate ...
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Statistical Models and Analysis of Univariate and Multivariate Degradation Data
... With advances in technology, both manufacturer and consumer have demanded greater product reliability. As a result, to improve customer satisfaction, accurate evaluation of the reliability of products plays an important ...
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Assessing Univariate and Multivariate Normality, A Guide For Non-Statisticians
... the statistics literature, the normality assumption is tagged as an omnipresent ...both univariate and multivariate analysis (Rosner, ...many multivariate statistical techniques such as, ...
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Univariate and Multivariate GARCH Models Applied to the CARBS Indices
... In a similar study, Oberholzer et al. (2015a) [20] used the standard GARCH, GJR-GARCH, and EGARCH to determine the best fitting model for the five indices of the Johannesburg Stock Exchange (JSE) before, during, and ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... of univariate bias- adjustment methods for multivariate ...our analyses are of a rather conceptual na- ture and thus also apply to other climate model outputs, for instance from regional climate ...
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Transformations for multivariate statistics
... in univariate Edgeworth series to the multivariate case+ To solve the system of differential equations that the transformation must satisfy, ~6!, more structure on the inferential problem was imposed, ...
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Topics In Multivariate Statistics
... correlation analysis (kernel CCA) (Bach & Jordan, 2003), a nonlinear extension of canonical correlation analysis, when there are only two variables of interest. The statistical convergence of kernel CCA was first ...
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Univariate and multivariate control charts for monitoring sugar production process
... a multivariate analogue of the univariate Student’s tdistribution ...charting statistics and then the statistic charting was known as HotellingT 2 ...
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Multivariate models for pretest posttest data and a comparison to univariate models
... is the error that is present but not specifically controlled for. As with the regressor variable approach, researchers need to deal with some issues when using this approach. First, the change score method is known to be ...
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