Partial least squares (PLS) is sometimes used as an alternative to covariance-based structural equation modeling (SEM). This paper briefly reviews currently available SEM techniques, and provides a critique of the perceived advantages of PLS over covariance-based SEM as commonly cited by PLS users. Specific attention is drawn to the primary disadvantage of PLS, namely the lack of consistency of...

Evaluation of the physico-chemical properties that affected the experimental data was performed for 45 newly synthesized compounds, derivatives of 2,4-dioksotetrahydro-1,3-thiazole. In order to quantify molecular structure various molecular descriptors were calculated for each of the 45 compounds. Evaluation of physico-chemical properties was done by the partial least-squares (PLS) regression. ...

quantitative relationships between molecular structure and azolo-adamantanes derivatives were discovered by different chemometric tools including factor analysis based multiple linear regressions (fa-mlr), principle component regression analysis (pcra), and genetic algorithm-partial least squares ga-pls. the fa-mlr describes the effect of geometrical and quantum indices on enzyme inhibition act...

We identify top management leadership, a sophisticated management infrastructure, process management efficacy, and stakeholder participation as important elements of a quality-oriented organizational system for software development. A model interrelating these constructs and quality performance is proposed. Data collected through a national survey of IS executives in Fortune 1000 companies and ...

Partial Least Squares (PLS) is a statistical technique that is widely used in the Partial Least Squares (PLS) is a popular technique for estimating structural equation models with latent variables. It is frequently perceived as an alternative to covariance analysis of such models. While its proponents recognize the shortcomings of PLS for testing explanatory models in comparison to covariance m...

the multivariate calibration method, partial least square regression (pls) was applied for thesimultaneous spectrophotometric determination of lidocaine (lid) and hydrocortisone acetate(hca) in their mixtures. the parameters of chemometric technique were optimized and theproposed method was validated with synthetic samples and applied to analyze these drugs inpharmaceutical products with good a...

Although methodology use generally leads to fewer software defects and reductions in development time, the introduction of a formalized systems development methodology is often met with substantial resistance. Motivated by the purported benefits of methodology use, yet resistance to the introduction of a methodology, this study explains developer attitude toward using a formalized commercial me...

Six simple, dynamic soft sensor methodologies with two update conditions were compared on two experimentally-obtained datasets and one simulated dataset. The soft sensors investigated were: moving window partial least squares regression (and a recursive variant), moving window random forest regression, feedforward neural networks, mean moving window, and a novel random forest partial least squa...

a University of North Carolina Wilmington, Cameron School of Business, 601 South College Road, Wilmington, NC 28403, United States b University of Nebraska at Omaha, The Peter Kiewit Institute, 1110 S 67th St., Omaha, NE 68182-0392, United States c University of North Texas, 1155 Union Circle #305219, Denton, TX 76203-5017, United States d Sam Houston State University, College of Business Admin...

a r t i c l e i n f o The key point in multivariate calibration is to build an accurate regression relationship between the predictors and responses. In this paper, we first use extreme learning machine (ELM) to build spectroscopy regression model. Then, we propose a combinational ELM (CELM) method in which the decision function is represented as a sum of a linear hidden-node output function (a...