SHORT COMMUNICATION CLASSIFICATION METHODS FOR MULTIVARIATE QUALITY PARAMETERS

There are many chemical products where product conformity is decided upon by qualitative humanjudgements of overall product quality.Nowadays,quantitative instrumentally determined qualityparameters become available which are intended to replace such qualitative judgements by means ofautomatic decision rules using multivariate specification limits.Six classification methods to derive suchlimits are compared in terms of their power to predict corresponding human judgements on overall colorconformity of 17 dyestuffs based on historical quality data.Standard statistical classification methodsturned out to be unacceptable for the routine generation of decision rules because of the frequent distinctsuboptimality of their predictive power.Instead,a simple non-statistical classification method utilizinga priori knowledge about the underlying data structure yielded uniformly satisfactory decision rules.     

Detection of ocean waves using satellite altimetry: Application to equatorial Kelvin waves

A new method for wave motion detection from satellite altimetric measurements of sea surface height is presented. The essence of the approach is to construct a two‐dimensional traveling‐wave Fourier series representation of the amplitude field within a prespecified oceanic region. The method employs an iterative, nonlinear least‐squares technique based on the Marquardt‐Levenberg algorithm to solve for model parameters describing characteristic features of the evolving wave system. The Marquardt‐Levenberg Fourier series (MLFS) algorithm was applied to Kelvin waves active during the 1986–1987 El Nino event in the equatorial Pacific ocean using GEOSAT Exact Repeat Mission altimetry data. Characteristics of the wave system were found to be in essential agreement with earlier field measurements and the observations of Cheney and Miller (1987) obtained using time series developed from GEOSAT data. The advantage of the present detection scheme lies in its speed and ability to determine a wave system's dispersion relation over a finite range of wavenumbers, and hence the group velocity of that system.     

REVIEW ARTICLE MULTIVARIATE EXPLORATORY DATA ANALYSIS AND GRAPHICS:A TUTORIAL

Exploratory data analysis(EDA)is a toolbox of data manipulation methods for looking at data to seewhat they seem to say,i.e.one tries to let the data speak for themselves.In this way there is hope thatthe data will lead to indications about'models'of relationships not expected a priori.In this respect EDAis a pre-step to confirmatory data analysis which delivers measures of how adequate a model is.In thistutorial the focus is on multivariate exploratory data analysis for quantitative data using linear methodsfor dimension reduction and prediction.Purely graphical multivariate tools such as 3D rotation andscatterplot matrices are discussed after having introduced the univariate and bivariate tools on which theyare based.The main tasks of multivariate exploratory data analysis are identified as'search for structure'by dimension reduction and'model selection'by comparing predictive power.Resampling is used tosupport validity,and variables selection to improve interpretability.     

High‐frequency streamflow acquisition and bed level/flow angle estimates in a mountainous river using shallow‐water acoustic tomography

The acquisition of reliable discharge estimates is crucial in hydrological studies. This study demonstrates a promising acoustic method for measuring streamflow at high sampling rate for a long period using the fluvial acoustic tomography system (FATS). The FATS recently emerged as an innovative technique for continuous measurements of streamflow. In contrast to the traditional point/transect measurements of discharge, the FATS enables the depth‐averaged and range‐averaged flow velocity along the ray path to be measured in a fraction of a second. The field test was conducted in a shallow gravel‐bed river (0.9 m deep under low‐flow conditions, 115 m wide) for 1 month. The parameters (stream direction and bottom elevation) required for calculating the streamflow were deduced by a nonlinear regression to the discharge data from the well‐established rating curve. The cross‐sectional average velocities were automatically calculated from the acoustic data, which were collected on both riverbanks every 30 s. The FATS was connected to the internet so that the real‐time flow data could be obtained. The FATS captured discharge variations at a cut‐off frequency of approximately 70 day^?1. The stream exhibited temporal discharge changes at multiple time scales ranging from a few tens of minutes to days. Copyright © 2016 John Wiley & Sons, Ltd.