Showing papers in "Chemometrics and Intelligent Laboratory Systems in 1995"

TL;DR: This paper uses a well-known ‘time lag shift’ method to include dynamic behavior in the PCA model and demonstrates the effectiveness of the proposed methodology on the Tennessee Eastman process simulation.

TL;DR: In this article, the application of multivariate curve resolution to second order data from hyphenated liquid chromatography with spectrometric diode array detection is shown, where the authors apply it to second-order data with different data structures depending on the reproducibility of the elution process.

TL;DR: Multivariate statistical procedures for monitoring the progress of batch processes are developed using multi-way partial least squares for extracting information from the process measurement variable trajectories that is more relevant to the final quality variables of the product.

TL;DR: Applications are provided on the analysis of historical data from the catalytic cracking section of a large petroleum refinery, on the monitoring and diagnosis of a continuous polymerization process and on the Monitoring of an industrial batch process.

TL;DR: In this article, the D-optimality concept is applied to select a design when the classical symmetrical designs cannot be used, such as when the experimental region is not regular in shape, when the number of experiments chosen by a classical design is too large or when one wants to apply models that deviate from the usual first or second order ones.

TL;DR: My views will be focussed on the role of chemometrics in chemistry, on how I see statistics as partly consistent, and partly inconsistent with the framework of chemistry, and where the authors should aim for the future.

TL;DR: In this article, the additive/multiplicative transformations conserve the area under the spectral curve, and the relationship between the multiplicative scatter and the standard normal variate transformations is investigated.

TL;DR: In this paper, the theory of model-free resolution of data matrices from hyphenated chromatography is considered, where the elution products of chromatography are simultaneously analyzed by spectroscopy.

TL;DR: In this article, the authors compare the performance of the smooth response surface method (SRS) and the alias k-nearest neighbors (k-NN) on a set of simulated compositional data with 100 training samples and 500 independent evaluation samples.

TL;DR: In this paper, a new theoretical three-dimensional molecular indices (weighted holistic invariant molecular (WHIM) descriptors) are defined and further developments of the theory are proposed and the WHIM descriptors are used for modeling properties of polyaromatic hydrocarbons (PAHs) such as melting point, boiling point and hydrophobicity.

TL;DR: A robust principal components regression procedure based on the ellipsoidal multivariate trimming (MVT) and the least median of squares (LMS) methods is proposed as an outlier detection tool.

TL;DR: In this article, a procedure for the transfer of the regression equation in near-infrared spectroscopy (NIRS), from a first instrument to a second instrument, is presented.

TL;DR: A method is proposed to estimate the sensitivity of network outputs to the amplitude of random errors in the input space, sampled from known normal distributions to select a neural network model which optimally approximates the nonlinear relations between objects in input and output space.

TL;DR: The neural networks employing the counter-propagation learning strategy are described and their use for making complex models and inverse models is explained and two examples show how such modelling strategy can yield satisfactory results.

TL;DR: In this critique the formula utilized in The Unscrambler II software, an ‘empirically found formula’ to express the uncertainty, underestimates the root mean squared error of prediction in most practical applications of PLS.

TL;DR: Quantitative tools that evaluate overlap and similarity between high-dimensional PCA models are proposed in this communication, and their implications on determining the discrimination power ofPCA models of processes operating under disturbances are discussed.

TL;DR: The tensor algebra and vector space geometry provide a unifying framework for multilinear data analysis, which simplifies notation and leads to economy of thought as mentioned in this paper, avoiding too much abstraction too soon in defining tensor products makes these concepts accessible.

TL;DR: In this paper, several nonparametric nonlinear regression models are discussed and compared and the performances of these methods are compared in a Monte Carlo simulation study and illustrated on a data set from food chemistry.

TL;DR: Recent chemometric approaches to most of these steps will be presented using data obtained from a process spectrometer installed on a polymer production unit, and possibilities for new or improved methodologies are discussed.

TL;DR: In this article, three different robust partial least squares (PLS) alternatives are compared in order to reduce the effect of outliers in high-dimensional data, and the results show that, although iteratively reweighted least squares, based on the biweight mean, offers efficiency in a variety of situations, in higher dimensions, there are still considerable deviations from the ordinary PLS solution without outliers.

TL;DR: The procedure is illustrated and compared to existing robust methods, using several data sets known to contain multiple outliers and its performance and robustness are additionally tested by a Monte Carlo study on the simulated data sets.

TL;DR: The potentials of partial least squares regression (PLS) as a tool for the automated interpretation of infrared spectra have been investigated in this paper, where class probabilities are obtained by applying a sigmoid function to the PLS predictions.

TL;DR: Cluster analysis and projections on latent variables provide a link between the two paradigms of pattern recognition which were described above, and it is hoped that chemometrics will be capable of producing a novel and persisting view of the world, in the same way as has been achieved in biometrics and in psychometrics.

TL;DR: In this article, a general method for evaluating the statistical degree of overlapping (SDO) in a multicomponent chromatogram, whose retention pattern is known and described by the frequency function of interdistances between subsequent single component peaks (interdistance model, IM), is reported.

TL;DR: In this article, the evolution factor analysis (EFA) procedure was used to obtain, in a self-modeling base, spectra and fluorescence intensity profiles for the detected binding sites.

TL;DR: In this article, the problems that potentially occur when one performs a partial least square (PLS) analysis on compositional data and suggests logcontrast partial least squares (LCPLS), as an alternative.

TL;DR: In this paper, the acid-base properties and the copper-II-complexing behavior of the polynucleotide polyinosinic acid have been studied by means of potentiometric and spectrophotometric titrations.

TL;DR: The efficiency of multi-layered feed-forward networks (MLF) on classification is evaluated by applying them to simulated data by performing an ANOVA of the experimental designs and by principal components and correspondence analysis.

TL;DR: The amino acid sequences for proteins with different final locations in Escherichia coli have significant features related to protein structure and location.

TL;DR: In this paper, an example of correct and incorrect use of multilinear regression is presented in detail the quality of the coefficients and the goodness of the prediction depend on the experimental design, and the value of R 2 gives no information at all about them.