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Showing 1 to 20 of 301 for “"partial least squares"”.
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The construction of a partial least squares biplot
… of data. Another possible employment is in Partial Least Squares (PLS). First introduced as a regression method, PLS is more flexible than multivariate regression, but better suited than Principal Component Regression (PCR) for the prediction of a set of response variables from a large set …
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Partial least squares structural equation modelling with incomplete data. An investigation of the impact of imputation methods.
… to assess the impact of missing values on partial least squares structural equation modelling (PLS-SEM) based on the estimated accuracy of both structural and measurement parameters. The best method to deal with particular missing data mechanisms is highly recognized. Several significant …
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Parametric Yield and Tolerance Optimisation of Electromagnetic Devices using Feature-based Non-Linear Partial Least Squares Polynomial Chaos Expansion Surrogates
… approach exploiting feature based non-linear partial least squares polynomial chaos expansion (NLPLS-PCE). In the proposed method, yield is approximated at the level of the feature points since the functional relationship between the feature points and geometrical parameters is much less …
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Bridging the Scale Gap: linking 2D proteomic and 3D tumour spheroid morphometric data using partial least squares structural equation modelling
Cancer is a leading health concern worldwide with approximately 17 million new cases in 2018. Treatment for cancer includes the use of chemotherapeutic drugs, radiation and surgery. Research into possible new therapeutics, and improvement of existing treatment for the different pathologies of …
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Using partial least squares approach to predict factors that contribute to the impact of e-folios on pre-service teachers' learning
… To analyze survey data, the researcher used the Partial Least Squares (PLS) approach to Structural Equation Modeling (SEM), which is a method for estimating the likelihood of the success of PASS-PORT given information about other factors that influence the use of PASS-PORT. (Falk & Miller, 1992). …
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Virtual technologies in nurse education: the pairing of critical realism with partial least squares structural equation modelling as an evaluation methodology.
… controlled trial (RCT) (n=171), analysed via Partial Least Squares-Structural Equation Modelling (PLS-SEM). The conceptual pathway model for this PLS-SEM approach was drawn from a Critical Realist (CR) review. Hence the main aim was to assess the effectiveness of CR paired with PLS-SEM as a …
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Investigation of a solvent-free continuous process to produce pharmaceutical co-crystals. Understanding and developing solvent-free continuous cocrystallisation (SFCC) through study of co-crystal formation under the application of heat, model shear and twin screw extrusion, including development of a near infrared spectroscopy partial least squares quantification method
… Finally, NIR spectroscopy was used to create two partial least squares regression models, for predicting the 1:1 co-crystal yield of ibuprofen – nicotinamide and carbamazepine – nicotinamide, when in a powder mixture with the respective pure API. It is believed that the prediction models created …
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2d quantitative structure activity relationship modeling of methylphenidate analogues using algorithm and partial least square regression
… of molecular conformation. A genetic algorithm - partial least squares (GA-PLS) approach was used to identify the molecular descriptors that correlate to the biological activity (binding affinity) of a set of 80 methylphenidate analogues and to construct a predictive model. The GA code was …
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Fast Identification of Components Commonly Used in Homemade Explosives by Spectroscopic and Chemometric Methods
… such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) for qualitative discrimination and classification of common fuel sources and inorganic salts used as oxidants. Additional quantification research was performed to determine limits of detection for …
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Applying secondary ion mass spectrometry to cellular and model membranes to image component distribution and quantify composition
… analysis (MVA). TOF-SIMS and the MVA method partial least squares discriminant analysis (PLS-DA) was used to identify the differentiation stage of hematopoietic cells. Since TOF-SIMS is a location-specific technique, it can be used to investigate how varying chemical and material environments …
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Statistical Surrogate Models for Robust Design Optimisation in Reduced Dimension
… Although conventional MVL methods such as partial least squares (PLS) are effective when embedded within GPs, they provide no error estimate when reconstructing from a low-rank approximation. This is addressed by probabilistic partial least squares (PPLS) which treats latent variables …
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Hyperspectral Imaging for Evaluation of Herring Stocks caught around Iceland
… these samples, 54 were NSSH and 26 were ISSH. Partial Least Squares Discriminant Analysis (PLS-DA) was utilized for the stock classification. The water content of the fish was predicted through the Partial Least Squares Regression (PLS-R) of the spectral data, compared to traditional analytical …
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Deriving statistical inference from the application of artificial neural networks to clinical metabolomics data
… multivariate linear projection methods, such as partial least squares discriminant analysis (PLS-DA) have become standard. Non-linear projections methods, typified by Artificial Neural Networks (ANNs) may be more appropriate to model potential nonlinear latent covariance; however, they are not …
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Inferences on high-dimensional data
… methods, principal components analysis (PCA) and partial least squares (PLS), are used for regression and classification. We show that the null distribution of the PLS ""f-test"" statistic, which is obtained from one factor PLS regression, depends heavily on the design. A simulation method is …
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Examining the psychometric characteristics of an instrument to measure the impact of the climate on health behavior: A pilot study based on the Behavioral Ecological Model
… in the study by completing a web-based survey. Partial Least Squares Confirmatory Factor Analysis (CFA) was conducted in order to examine the psychometric characteristics of the instrument. Kruskal-Wallis H tests and Mann-Whitney U tests were utilized in order to examine differences, based on …
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Factores que determinan la intención de uso y el uso de entornos b-learning que utilizan herramientas colaborativas: Aplicación de UTAUT a la Academia CISCO
… la regresión por mínimos cuadrados parciales (Partial Least Squares, PLS).
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Identifying the intervening variables in the information technology investment and organizational performance relationship
… McKeen (1993) Results of data analysis using the Partial Least Squares technique are presented and discussed. Findings suggest that the Technology to Performance Chain does act as an intervening variable in the IT investment/organization performance relationship. Limitations of the present study, …
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Degradation analyses of empirical inferential predictors for the development of improved dynamic mechanistic/empirical equations
… forests, gradient boosting, neural networks and partial least squares, to optimize the prediction accuracy and process control. By leveraging these models, the study aims to enhance the automation and optimization of process units within chemical process plants, ultimately contributing to the …
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Espacio de diseño con métodos de inversión de modelos de regresión sobre variables latentes
… inversión de modelos predictivos del tipo PLS (Partial Least Squares) mediante un procedimiento computacional basado en algoritmos evolutivos. Se explora el impacto del espacio residual asociado a las variables predictoras sobre las soluciones obtenidas al invertir el modelo caracterizando así …
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Neural Correlates of Repetition Priming: Changes in fMRI Activation and Synchrony
… an independent functional localizer. Then, Seed Partial Least Squares was used to assess task-related functional connectivity of these regions across repetition of stimuli from multiple categories during an independent semantic classification task. While the results did not show the hypothesized …
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