Univariate and Multivariate Analysis Tasks Completed
Tasks for multivariate network analysis
... level tasks and not a complete list. These tasks are not specific to multivariate networks and are biased towards exploration and ...where multivariate networks are of interest, performing a ...
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Statistical Models and Analysis of Univariate and Multivariate Degradation Data
... For degradation data in reliability analysis, estimation of the first-passage time (FPT) distribution to a threshold provides valuable information on reliability characteristics. Re- cently, Balakrishnan and Qin ...
180
Comparison of univariate and multivariate linkage analysis of traits related to hypertension
... a univariate and multivariate linkage approach to analyze SBP or traits related to HTN (and highly correlated with SBP) - TG, LDL, and HDL, ...linkage analysis identified more nominally significant ...
5
Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models
... As mentioned above, alternative block sampling strategies to simulate Λ|R, ω are Shephard and Pitt’s (1997) multi-move sampler and the mixture sampler of Kim et al. (1998). The multi-move sampling procedure divides the ...
26
Classical and Bayesian Analysis of Univariate and Multivariate Stochastic Volatility Models
... As mentioned above, alternative block sampling strategies to simulate Λ|R, ω are Shephard and Pitt’s (1997) multi-move sampler and the mixture sampler of Kim et al. (1998). The multi-move sampling procedure divides the ...
24
Univariate and multivariate pattern analysis of preterm subjects: a multimodal neuroimaging study
... using univariate and multivariate pattern ...the univariate model of the amplitude of low-frequency BOLD fluctuations (ALFF) and gray matter volume (GMV) making use of resting-state fMRI and ...
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Predictive factors for infertility of women: an univariate and multivariate logistic regression analysis
... present study, the univariate and multivariate logistic regression showed that the husband’s education could be considered as a predictor of female infertility. In most cases, higher income levels have been ...
8
Univariate and Multivariate Time Series Manifold Learning
... series analysis aims to extract meaningful information from data that has been generated in sequence by a dynamic ...component analysis where fewer components are retained in order to identify the ...
18
Shapelet Transforms for Univariate and Multivariate Time Series Classification
... In support of this thesis a new distance early abandon method is proposed. A class balancing algorithm is implemented, which uses a one vs. all multi class information gain that enables heuristics which were developed ...
182
Essays on univariate and multivariate modeling of financial market risks
... While there are plenty of studies on the characteristics of financial time-series data in the econometrics literature, modeling internet search queries has not yet been suf- ficiently investigated. At the model ...
240
The effect of univariate bias adjustment on multivariate hazard estimates
... to analysis. The studied time period is 1981–1995. Our analysis is based on daily val- ues during the hottest month of the year at each grid point, which results in about 450 ...our analysis ...
13
Assessing Univariate and Multivariate Normality, A Guide For Non-Statisticians
... both univariate and multivariate analysis (Rosner, ...t-tests, Analysis of Variance (ANOVA), just to name a few, are based on the normal distribution (Neter et ...many multivariate ...
8
Univariate and Multivariate GARCH Models Applied to the CARBS Indices
... ferent univariate and multivariate GARCH family ...empirical analysis, the symmet- ric GARCH, and asymmetric GJR-GARCH and EGARCH models were estimated for the CARBS indices and a global minimum ...
16
The effect of univariate bias adjustment on multivariate hazard estimates
... of univariate bias- adjustment methods for multivariate ...traditional univariate bias-adjustment methods gen- erally reduce biases in impacts that depend on multiple de- pendent ...use ...
13
Simple techniques for likelihood analysis of univariate and multivariate stable distributions: with extensions to multivariate stochastic volatility and dynamic factor models
... In the case of general (non-symmetric) multivariate stable distributions the samples. , so estimates , 0 can be obtained along with and.[r] ...
61
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 ...
61
Evaluation of genetic diversity among soybean (Glycine max) genotypes using univariate and multivariate analysis.
... Twenty-four soybean genotypes were evaluated, and of these, 17 were lineages proceeding from the Soybean Breeding Program of Universidade Federal de Uberlândia, and 7 were commercial c[r] ...
10
Multivariate models for pretest posttest data and a comparison to univariate models
... 1.2 Univariate methods Due to the popularity of this research design, di↵erent methods have been developed in order to evaluate the data while accounting for ...the analysis of the posttest ...
25
Comparing univariate and multivariate models to forecast portfolio value-at-risk
... whether multivariate or univariate models are most appropriate for the problem of portfolio VaR ...that multivariate GARCH models outperformed competing univariate models on an out-of-sample ...
30
Temporal aggregation of univariate and multivariate time series models: A survey
... 8 The original cash deficit time series, in nominal terms, has been deflated dividing by the monthly Belgian CPI, base year 1996. 9 We use the package TRAMO to fit the best model. TRAMO (Time Series Regression with ARIMA ...
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