Sentence examples for multivariate methods and from inspiring English sources

We used multivariate methods and diversity indices for a general analysis, comprising both species richness and the species composition of assemblages.

The aims of this study were to i) to compare the influence of preprocessing techniques on prediction performance, ii) assess the modeling performance of a wide range of multivariate methods, and iii) evaluate the potential of Vis-NIR spectroscopy to predict SOC.

His previously published work includes Exchange Rate Volatility in Emerging Economies, Quantitative Analysis and IBM® SPSS® Statistics, and Multivariate Methods and Forecasting with IBM® SPSS® Statistics.

His previously published work includes Exchange Rate Volatility in Emerging Markers, Quantitative Analysis, Multivariate Methods & Forecasting with IBM SPSS Statistics and Multivariate Methods and Forecasting with IBM® SPSS® Statistics.

The problem of environmental data reduction and interpretation of multiconstituent physicochemical and biochemical measurements can be more easily handled through application of robust multivariate methods and exploratory data analysis (Brown 1988; Wenning and Erickson 1994).

PCA is one of the more straightforward multivariate methods and is primarily used to reduce dimensionality in data sets by 'concentrating' variation into fewer uncorrelated variables.

The multivariate methods described and used herein rely on linear algebraic operations and are transparent in contrast to neural nets (for example), which are often seen as black boxes.

Two multivariate methods, FA and PCA, were used for data calculation, separately for the control and patient groups, with 19 dimensions presenting percentage of the dog's indications and 18 for VOCs.

Methods covered include multivariate methods (PCA and extensions), sparse representations (trees, networks, contingency tables) as well as nonparametric testing (Bootstrap, permutation and Monte Carlo methods).

There are several methods to remove outliers from true data including statistical methods such as univariate and multivariate methods, Minkowski error, and signal processing methods such as wavelet, transform (Aggarwal 2013).

Findings were analyzed using bivariate and multivariate methods of the associations and determinants of health worker motivation and retention.