Search results for "Multivariate statistics"
showing 10 items of 290 documents
A statistical approach towards a regionalization of daily rainfall in Sri Lanka
1993
Regionalization of daily rainfall in Sri Lanka was examined using orthogonal factor analysis (OFA) based on daily rainfall data of 42 stations for a 15-year period (1971–1985). The number of potential rainy days was computed from the original data matrix and subjected to S-mode OFA. The first 10 orthogonal factors were shown as highly significant, explaining 65.1 per cent of the total variance of the whole data matrix, where the level of eigenvalues represented was > 1.0. Noticeably, the 10 orthogonal factors clearly revealed the different homogeneous daily rainfall regions in Sri Lanka (labelled as A to J), according to the orthogonal factor high loadings matrix. Delimitation of the daily …
Multivariate nonparametric tests in a randomized complete block design
2003
AbstractIn this paper multivariate extensions of the Friedman and Page tests for the comparison of several treatments are introduced. Related unadjusted and adjusted treatment effect estimates for the multivariate response variable are also found and their properties discussed. The test statistics and estimates are analogous to the traditional univariate methods. In test constructions, the univariate ranks are replaced by multivariate spatial ranks (J. Nonparam. Statist. 5 (1995) 201). Asymptotic theory is developed to provide approximations for the limiting distributions of the test statistics and estimates. Limiting efficiencies of the tests and treatment effect estimates are found in the…
Multivariate factor analysis of Girgentana goat milk composition
2005
The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs to the multivariate groups; for our study this particular statistical approach was employed. A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July, and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.…
Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression
2016
In Hettmansperger and Randles (Biometrika 89:851–860, 2002) spatial sign vectors were used to derive simultaneous estimators of multivariate location and shape. Oja (Multivariate nonparametric methods with R. Springer, New York, 2010) proposed a similar approach for the multivariate linear regression case. These estimators are highly robust and have under general assumptions a joint limiting multinormal distribution. The estimates are easy to compute using fixed-point algorithms. There are however no exact proofs for the convergence of these algorithms. The existence and uniqueness of the solutions also still remain unproven although we believe that they hold under general conditions. To ci…
The Age-Participation Relationship Revised: Focus on Older Adults
1998
This study aims to increase our understanding of how the negative influence of age on participation comes about. The framework used emphasizes human life complexity and human agency in behavior and decision-making. Accordingly, main effects and multiple interaction effects of age and some education and work-related factors on participation were examined. The results show that when the interaction effects are taken into account, the age-participation relationship becomes more complex than previously found in studies focusing only on main effects. It is suggested that research on participation utilize the more advanced options available in multivariate statistics and thus aim at better compa…
Imputation Strategies for Missing Data in Environmental Time Series for An Unlucky Situation
2005
After a detailed review of the main specific solutions for treatment of missing data in environmental time series, this paper deals with the unlucky situation in which, in an hourly series, missing data immediately follow an absolutely anomalous period, for which we do not have any similar period to use for imputation. A tentative multivariate and multiple imputation is put forward and evaluated; it is based on the possibility, typical of environmental time series, to resort to correlations or physical laws that characterize relationships between air pollutants.
Comparison of different predictive models for nutrient estimation in a sequencing batch reactor for wastewater treatment
2006
Abstract In this paper different predictive models for nutrient estimation in a sequencing batch reactor (SBR) for wastewater treatment are compared: principal component regression (PCR), partial least squares (PLS), and artificial neural networks (ANNs). Two unfolding procedures were used: batch-wise and variable-wise. For the latter unfolding method, X and Y matrix augmentation with lagged variables were used in some models to incorporate process dynamics. The results have shown that batch-wise unfolding PLS models outperform the other approaches. The ANN models are good predictive models, but in this particular case-study, they do not outperform those multivariate projection models that …
Assessing directional interactions among multiple physiological time series: The role of instantaneous causality
2012
This paper deals with the assessment of frequency domain causality in multivariate (MV) time series with significant instantaneous interactions. After providing different causality definitions, we introduce an extended MV autoregressive modeling approach whereby each definition is described in the time domain in terms of the model coefficients, and is quantified in the frequency domain by means of novel measures of directional connectivity. These measures are illustrated in a theoretical example showing how they reduce to known indexes when instantaneous causality is trivial, while they describe peculiar aspects of directional interaction in the presence of instantaneous causality. The appl…
Comparison of canonical variate analysis and principal component analysis on 422 descriptive sensory studies
2015
International audience; Although Principal Component Analysis (PCA) of product mean scores is most often used to generate a product map from sensory profiling data, it does not take into account variance of product mean scores due to individual variability. Canonical Variate Analysis (CVA) of the product effect in the two-way (product and subject) multivariate ANOVA model is the natural extension of the classical univariate approach consisting of ANOVAs of every attribute. CVA generates successive components maximizing the ANOVA F-criterion. Thus, CVA is theoretically more adapted than PCA to represent sensory data. However, CVA requires a matrix inversion which can result in computing inst…
Structural invariants for the prediction of relative toxicities of polychloro dibenzo-p-dioxins and dibenzofurans
2004
Multivariate models are reported that can predict the relative toxicity of compounds with severe environmental impact, namely polychloro dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs). Multiple linear regression analysis (MLR) and partial least square projections of latent variables (PLS) show the usefulness of graph-theoretical descriptors, mainly topological charge indices (TCIs), in these series. The general trends of the group are correctly reproduced and better results are presented than have previously been published. In general, the more toxic compounds exhibit more symmetric molecular structures.