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44 results for “least squares method”
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Research ArticleOpen accessIn the abstractPredicting Microbe-Drug Association based on Similarity and Semi-Supervised LearningLingzhi Zhu, Jun Wang, Guixiang Li et al.Increasing clinic evidences have showed that microbial communities play important roles in human health and disease. Predicting hidden microbe-drug associations can be helpful in understanding the microbe-drug association mechanisms in clinical treatment, drug discovery, combinations and repositioning. Some computational methods were proposed to predict the associations of microbes and drugs. However, the prediction performance of these methods needs to be … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 9 Mar 2021 · 7,535 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Cryptography with Least Squares ApproximationsMustafa K. Ramadhan, Adil AL-RammahiSecurity of digital images has become one of the most important issues in network technologies. Different techniques have been evolved over the past few years to provide security for digital images through concealing information, image scrambling and image encryption. The aim of this work is to enhance the network security level by using the cryptographic method based on the Least … …Journal of Computer Science, Vol. 15, Issue 11 · 20 Nov 2019 · 7,330 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo-Stage Estimation in Inverse Problems using Combined Wavelet Thresholding and Penalized Maximum LikelihoodRobert G Aykroyd, Hassan AljohaniInverse problems occur in a wide range of practical scientific investigations where the variables of interest are only observed indirectly, such as magnetic and seismic imaging in geophysics, electrical tomography in industrial process monitoring, or PET scanning in medicine. Linear inverse problems can be thought of as highly multivariate regression problems with strong multicollinearity where the aim is to interpret … …Journal of Mathematics and Statistics, Vol. 13, Issue 3 · 29 Sep 2017 · 7,925 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeast Absolute Deviation Regression and Least Squares for Modeling Retention Indices of Set Compounds Food and Pollutants of the EnvironmentFatiha Mebarki, Khadija Amirat, Salima Ali Mokhnach, Djellol MessadiConsidering the importance of the statistical analysis of regression in modeling based separately on study for Quantitative structure retention indices on Carbowax 20 M (ICw20M) and OV-101 columns (IOV-101) relationships (QSRR) are determined for 114 pyrazines. The detection of influential observations for the standard least squares regression model is a problem which has been extensively studied. Least Absolute Deviation regression … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 5 Jun 2017 · 7,424 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeneral Linear Models in a Missing Outcome Environment of Clinical Trials Incorporating with Splines for Time-Invariant Continuous AdjustmentMinjeong Park, Dejian Lai, Xianglin L. Du et al.Missing data is a common occurrence in longitudinal studies of health care research. Although many studies have shown the potential usefulness of current missing analyses, e.g., (1) Complete Case (CC) analysis; (2) imputation methods such as Last Observation Carried Forward (LOCF), multiple imputations, Expectation-Maximization algorithm approach; and (3) methods using all available data such as linear mixed model and generalized … …Current Research in Biostatistics, Vol. 5, Issue 1 · 18 Aug 2015 · 7,401 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenetic Algorithm for Variable and Samples Selection in Multivariate Calibration ProblemsKelton de Souza Santiago, Anderson Silva Soares, Telma Woerle de Lima et al.One of the main problems of quantitative analytical chemistry is to estimate the concentration of one or more species from the values of certain physicochemical properties of the system of interest. For this it is necessary to construct a calibration model, i.e., to determine the relationship between measured properties and concentrations. The multivariate calibration is one of the most successful … …Journal of Computer Science, Vol. 11, Issue 4 · 8 Jun 2015 · 7,381 accessesView PDFCite
Research ArticleOpen accessIn the abstractRural and Urban Attitudes toward Immigrants in the U.S. Midwest and Great PlainsMiguel Ceballos, Oksana Yakushko, Courtney LyonsRecent immigration has transformed much of the Midwest and Great Plains regions of the United States, affecting its rural and urban areas through dramatic increases in the foreign-born population and in particular Latino immigrant populations. This study examines three theories of prejudice: Perceptions of threat, contact with immigrants and a cosmopolitanism outlook, in predicting rural and urban attitudes toward immigrants … …Journal of Social Sciences, Vol. 10, Issue 4 · 7 Jan 2015 · 8,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractMODEL SELECTION VIA ROBUST VERSION OF R-SQUAREDShokrya SalehR-squared (R2) is a popular method for variable selection in linear regression models. R2 based on Least Squares (LS) regression minimizes the sum of the squared residuals; LS is sensitive to outlier observation. Alternative criterion based on M-estimators, which is less sensitive to outlying observation has been proposed. In this study explicit expression for such criterion is obtained when the … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 9 Oct 2014 · 7,460 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NOVEL ROBUST AND EFFICIENT TOOL FOR DETECTING HETEROSCEDASTICITYWei Xiong, Maozai TianOne of the greatest values of Quantile Regression (QR) is that it provides a good procedure in the sense that QR could be much more efficient and sometimes arbitrarily more efficient in recovering the mean function than the Least Squares (LS) even when without moment conditions. However, heteroscedasticity definitely causes conditional variances of parametric or nonparametric estimates of mean functions … …Journal of Mathematics and Statistics, Vol. 10, Issue 2 · 21 Mar 2014 · 6,657 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE OF RIDGE REGRESSION ESTIMATOR METHODS ON SMALL SAMPLE SIZE BY VARYING CORRELATION COEFFICIENTS: A SIMULATION STUDYAnwar Fitrianto, Lee Ceng YikWhen independent variables have high linear correlation in a multiple linear regression model, we can have wrong analysis. It happens if we do the multiple linear regression analysis based on common Ordinary Least Squares (OLS) method. In this situation, we are suggested to use ridge regression estimator. We conduct some simulation study to compare the performance of ridge regression estimator … …Journal of Mathematics and Statistics, Vol. 10, Issue 1 · 3 Jan 2014 · 8,540 accessesView PDFCite