Some comparisons between multivariate and univariate techniques
Dispersion control for multivariate processes - some comparisons
... Statistical Performance of MLRT, SSVPC, MLRTECM and jsj 112 Charting Technique when L Shifts Along The Principal Axes. The eigenvalues of Lo~ L 1 L~t are the solutions[r] ...
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Multivariate trend comparisons between autocorrelated climate series with general trend regressors
... comparison between models and observations needs to take into account the ...consistency between the models and ...than some measure of central tendency it is impossible to draw any conclusions about ...
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Stochastic comparisons of stratied sampling techniques for some Monte Carlo estimators
... 7.2 Multivariate functions In this section we extend the results in Section ...but some restric- tions are necessary, both on the distribution of the random vector used for sampling and on the stratifying ...
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Comparing univariate and multivariate models to forecast portfolio value-at-risk
... pairwise comparisons among only multivariate and among only uni- variate ...among multivariate models indicates that dynamic conditional correlation models are preferred to the constant conditional ...
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Bias in Estimating Multivariate and Univariate Diffusions
... spondence between A( ) and F , requires the structural matrix A( ) to be ...and some of its eigenvalues are complex, A( ) is not uniquely ...relations between the ele- ments of a row of ...
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Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models
... In univariate stable Paretian distributions, implementation of ABC is conceptually straightforward although certain problems remain open and must be addressed: First, the choice of a proposal distribution for the ...
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On Comparison of Some Imputation Techniques in Multivariate Data Analysis
... relationship between the probability of Type II error, β and statistical power (1- β), we can say that the MI has not been able to appropriately tackle the issue of reduced power in this ...Though, some ...
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Comparisons between different techniques for measuring mass segregation
... This method suffers three significant drawbacks. One is that it requires a ‘centre’ to be defined. In relaxed, virialised star clusters there is a centre from which this can be mea- sured, but in substructured and messy ...
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Shapelet Transforms for Univariate and Multivariate Time Series Classification
... split between each ...on some of the very large datasets, especially the highly dimensional PEMS dataset, the number of shapelets available to each transform is still very ...from techniques such as ...
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On the Univariate Representation of Multivariate Volatility Models with Common Factors
... 3 some multivariate models accounting for co-movements and show that the implied marginal volatility processes are of low ...discriminate between a diagonal model and a general multivariate ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison ...
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Statistical Models and Analysis of Univariate and Multivariate Degradation Data
... improved techniques based on saddlepoint approximation, which enhance upon their suggested ...proposed techniques. Limitations of the improved techniques are discussed and some possible ...
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The effect of univariate bias adjustment on multivariate hazard estimates
... Whether univariate bias-adjustment methods effectively improve estimates of impacts that depend on multiple drivers is largely unknown, and the lack of long-term impact data prevents a direct comparison ...
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Temporal aggregation of univariate and multivariate time series models: A survey
... as a function of the aggregation frequency k. 23 The bottom panels of Figure 4 display the behaviour of the elements of the B ∗ and A ∗ parameter matrices for k=2, 3, . . ., 100. For each of the 99 values of k, the ...
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Adaptive Control Charts For Monitoring The Univariate And Multivariate Coefficient Of Variation
... In a real manufacturing process, the characteristics, such as the dimension, shape and central tendency of the distribution of two identical products will not be exactly similar. There will be some variation ...
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Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study
... integration between machine learning approach and medical imaging have been recently studied and tested in different clinical ...conventional univariate analysis methods, such as statistical tests that are ...
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Univariate versus Multivariate Models for Short-term Electricity Load Forecasting
... the univariate and multivariate models, we use a nonparametric test to see if the differences between their post-sample accuracies are statistically significant (that is, if we can say, with ...
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Fuzzy clustering of univariate and multivariate time series by genetic multiobjective optimization
... using some mathematical ...numerical techniques may be devised that are more efficient and ...similar multivariate time series and detect properties that multivariate time series in a group ...
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Univariate and multivariate Pareto models
... The survey presented in this paper is far from complete. A more detailed and extensive survey (though somewhat out of date) can be found in Arnold (1983). A revision of that book is, however, currently in preparation. In ...
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Stochastic Volatility: Univariate and Multivariate Extensions
... Corresponding Author: Éric Jacquier, Finance Department, Fulton Hall 224B, Boston College, Chestnut Hill, MA 02167, USA Tel: 617 552-2943 Fax: 617 552-0431 email: [email protected][r] ...
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