Antitubercular activity of Sulfathiazole Derivitives series were subjected to Quantitative Structure Activity Relationship (QSAR) Analysis with an attempt to derive and understand a correlation between the Biologically Activity as dependent variable and various descriptors as independent variables. QSAR models generated using 28 compounds. Several statistical regression expressions were obtaine...

Antitubercular activity of 5-nitrofuran-2-yl Derivatives series were subjected to Quantitative Structure Activity Relationship (QSAR) Analysis with an effort to derive and understand a correlation between the biological activity as response variable and different molecular descriptors as independent variables. QSAR models are built using 40 molecular descriptor dataset. Different statistical re...

PLS regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. Its goal is to predict or analyze a set of dependent variables from a set of independent variables or predictors. This prediction is achieved by extracting from the predictors a set of orthogonal factors called latent variables which have the best predictive pow...

the current study aims to identify and examine the effect of market orientation, management innovation and technological innovation on organizational performance. the current research was conducted using descriptive- correlational methodology. the population of the current research included pharmaceutical companies throughout the country. using simplerandom sampling method and cochran formula, ...

Partial least squares path modeling (PLS) has seen increased use in the information systems research community. One of the stated key advantages of PLS is that it weights the indicator variables based on the strength of the relationship between the indicators and the underlying constructs, which presumably decreases the effect of measurement error in the analysis results. In this paper we argue...

Improving the ability to assess potential stroke deficit may aid the selection of patients most likely to benefit from acute stroke therapies. Methods based only on ‘at risk’ volumes or initial neurological condition do predict eventual outcome but not perfectly. Given the close relationship between anatomy and function in the brain, we propose the use of a modified version of partial least squ...

Simultaneous determination of difloxacin and enrofloxacin using two chemometric methods, partial least squares regression (PLS) and direct orthogonal signal correction-partial least squares regression (DOSC-PLS) is described in this paper. The simultaneous determination of these drugs is difficult due to spectral interferences. The calibration graphs were linear in the range of 1-10 μg mL-1 and...

An objective wavelength selection method is proposed for near-infrared (NIR) spectroscopy mainly to overcome the possible subjectivity introduced by moving window partial least squares regression (MWPLS). This improved procedure (iMWPLS) introduced an indicator to evaluate importance of each wavelength and then all wavelengths were ranked by these indicators. On the basis of the indicator ranki...

Partial least squares (PLS) regression is commonly used for multivariate calibration of instruments. Because of the need to know the quality of the prediction in a specific unknown sample and the lack of theory, an 'empirically found formula' to express the uncertainty is utilized in The Unscrambler II software, the de-facto standard in computer software for PLS. In this critique the formula is...

Univariate partial least squares (PLS) is a method of modeling relationships between a Y variable and other explanatory vanables. It may be used with any number of explanatory variables, even far more than the number of observations. A simple interpretation is given that shows the method to be a straightforward and reasonable way of forming prediction equations. Its relationship to multivariate...