Partial Least Squares (SEM) Regression
Study on Partial Least-Squares Regression Model of Simulating Freezing Depth Based on Particle Swarm Optimization
... building partial least squares regression model, how many components should be selected on earth? Whether it has remarkable improvement for the model’s forecasting function after adding one ...
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Speech Emotion Recognition with MPCA and Kernel Partial Least Squares Regression
... Abstract—Speech signal is one of the major means for communication which carries not only semantic, but personal information , such as genders and emotions. The researches about speech emotion have become more and more ...
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The Jackknife Interval Estimation of Parametersin Partial Least Squares Regression Modelfor Poverty Data Analysis
... fitted regression model. Common classical regression technique by using Least Squares estimate is highly sensitive to multicollinearity ...area, Partial Least Squares ...
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Detection of sclerotinia rot disease on celery using hyperspectral data and partial least squares regression
... Partial Least Square Analysis of Norris First Derivative. Table 2 presents the PLS regression results of celery disease and Norris first derivative values. The explained Y variances vary from 95.48% ...
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Determination of Hexazinone in Environmental Samples by Uv-Vis Spectrophotometry-Partial Least Squares Regression
... 15. Ferrand M., Huquet B., Barbey S., Barillet F., Faucon F., Larroque H., Leray O., Trommenschlager J.M. and Brochard M., Determination of fatty acid profile in cow's milk using mid-infrared spectrometry: Interest of ...
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Development of a robust hybrid estimator using partial least squares regression and artificial neural networks.
... The aim of this paper is ro develop a robust inferentjal estimator by usjng hybrid PLS-ANN model based on on-line measuements of process variables, such as flow raies and temperatur[r] ...
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Kernel Partial Least Squares Regression in Reproducing Kernel Hilbert Space
... Both multivariate and univariate regression models were studied. Multivariate kernel PLS tries to find components that are good predictors for all response variables. In the final model the same components are used ...
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1. Simultaneous determination of drugs used for chronic active gastritis disease by chemometric methods
... Clarithromycin [1], amoxicillin [2] and lansoprazole [3] are used for eradication of gastrointestinal system infection with Helicobacter pylori (HP) [4]. Helicobacter pylori (HP), a gram-negative bacterium incorporated ...
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Comparison of Different Regularized and Shrinkage Regression Methods to Predict Daily Tropospheric Ozone Concentration in the Grand Casablanca Area
... Linear Regression (MLR) that circumvent the problem of multicollinearity which is likely to lead to unstable ...regularized regression me- thods: Principal Components Regression [14], Partial ...
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SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF RABEPRAZOLE SODIUM AND DOMPERIDONE MALEATE IN CAPSULES BY CHEMOMETRIC METHODS
... Digitized UV/VIS absorbency spectra were collected using a UV-visible spectrometer 2300Techcomp with 1cm quartz cells. The data acquisition was made with UV solutions software at a scan rate of 1000nm min−1 and the slit ...
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On the ease of predicting the thermodynamic properties of beta-cyclodextrin inclusion complexes
... statistical regression methods, namely principal components regression (PCR) [14], partial least squares regression (PLSR) [14] and support vector regression with forward ...
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Applicability of supervised discriminant analysis models to analyze astigmatism clinical trial data
... fitting partial least squares regression discriminant analysis, a preliminary principal component analysis was done for data ...the partial least squares regression ...
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Handling Multicollinearity; A Comparative Study Of The Prediction Performance Of Some Methods Based On Some Probabiltiy Distributions
... compared partial least squares regression, principal component regression, ridge regression and multiple linear regression methods in modeling and predicting daily mean ...
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Predicting the quality of ryegrass using hyperspectral imaging
... This study examines the utility of Hyperspectral Imag- ing (HSI) based methods for non-invasive assessment of the composition of ryegrass. The quality of forage is an important component of animal performance and envi- ...
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Functional Analysis of Chemometric Data
... by least squares approximation (spline regression) on the observ- ed absorbance at different wavelengths ...Second, least squares estimation of the parameters of model ...or ...
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The Relationship between Intellectual Capital, Firm Value and Transparency
... "partial least squares regression method" suggests that regardless of the corporate size, debt structure and past financial performance, there is a significant positive relationship ...
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A Comparative Study On Some Methods For Handling Multicollinearity Problems
... In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory ...in regression analysis. ...
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Study on the Concentration Inversion of NO & NO2 Gas from the Vehicle Exhaust Based on Weighted PLS
... [6] Yu, X.Y., Zhang, Y.J., Yin, F.G., Zhao, N.J., Duan, J.B., Xiao, X., Shi, Z.Y. and Fang, L. (2014) The Algae Fluorescence Spectrum Characteristic Wavelength of Partial Least Squares ...
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Comparative qsar analysis of histone deacetylase 6 (hdac6) inhibitors as anti cancer agents
... Linear Regression (MLR), Principal Component Regression (PCR) besides Partial east Squares regression (PLS) methods, in addition to a 3D QSAR model which was developed ...linear ...
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Partial Least Squares in Constructing Candidates Model Averaging Muhammad Arna Ramadhan, Bagus Sartono, Anang Kurnia
... Model averaging could be better choice in regression analysis when number of observations is much smaller the number of explanatory variables. Our method, PLSMA was developed to construct candidate models in model ...
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