نتایج جستجو برای: pls partial least squares application
تعداد نتایج: 1339124 فیلتر نتایج به سال:
Partial Least Squares (PLS) is a statistical technique that is widely used in the Information Systems discipline to estimate statistical models with structural equations and latent variables. While PLS does not provide a statistical test of model fit to data, its proponents have suggested a set of criteria that good PLS models should fulfill. Conversely, when a model does not satisfy these crit...
Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS multi-group analysis solely allow to assess di...
1. Methods to be considered for multivariate calibration Many methods for multivariate calibration have been proposed. It turns out that many of the methods perform similarly. To avoid confusion due to use of many different methods, it is suggested that only the following should be considered: Multiple linear regression (MLR) Principal component regression (PCR) Partial least squares (PLS) Neur...
Using the technology acceptance model (TAM), this study examined the external variables of technological complexity (TC) to acquire a better understanding of the factors that influence the acceptance of computer application courses by learners at Active Aging Universities. After the learners in this study had completed a 27-hour Facebook course, 44 learners responded to a modified TAM survey. D...
In the present work, an artificial neural network (ANN) model was used to study the quantitative structure retention relationship (QSRR) of retention index (RI) of some volatile compounds in natural cocoa and conched chocolate powder. Molecular structural descriptors are selected using genetic algorithm to construct the nonlinear QSRR models, kernel partial least squares PLS (KPLS) and Levenber...
Panax ginseng C.A. Meyer is a herb used for medicinal purposes, and its discrimination according to cultivation age has been an important and practical issue. This study employed Fourier-transform infrared (FT-IR) spectroscopy with multivariate statistical analysis to obtain a prediction model for discriminating cultivation ages (5 and 6 years) and three different parts (rhizome, tap root, and ...
A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While maintaining all the strengths of PLS, the consistent version provides two key improvements. Path coefficients, parameters of simultaneous equations, construct correlations, and indicator loadings are estimated consistently. The global goodness-of-fit of the structural model can also now be assessed,...
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. ...
This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices. In order to illustrate the behavior of the goodness-of-fit index (GoF) and the relative goodness-of-fit index (GoFrel), we estimate PLS path models with simulated data, and contrast their values with fit indices commonly used in covariance-based structural equation modeling. T...
The paper presents a specialised Partial Least Squares (PLS) algorithm for on-line calibration monitoring. At first, the basic scheme and philosophy of PEANO (Process Evaluation and Analysis by Neural Operators), an on-line calibration monitoring system, is briefly discussed. Then the reader gets introduced into the general idea of PLS, followed by an extension to Neural Network PLS (NNPLS). Th...
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