Search results for "Multivariable calculus"
showing 10 items of 21 documents
ChemInform Abstract: Discrimination and Molecular Design of New Theoretical Hypolipaemic Agents Using the Molecular Connectivity Functions.
2010
The molecular topology model and discriminant analysis have been applied to the prediction and QSAR interpretation of some pharmacological properties of hypolipaemic drugs using multivariable regre...
Calculation of chromatographic properties of barbiturates by molecular topology
1995
A study has been made of the relationship between the RF values obtained by thin layer chromatography for a group of barbiturates and the connectivity indices proposed by Kier and Hall. By using multivariable regression we obtained the corresponding connectivity functions, which were selected on the basis of their respective statistics parameters. The regression analysis of the connectivity functions shows a correct prediction of the experimental elution sequence for this group of molecules on silicagel with two mobile phases of different polarity. The corresponding random and stability studies of the different prediction models selected were carried out, demonstrating good stability and nu…
Prediction of chromatographic parameters for some anilines by molecular connectivity
1995
The possible relation existing between RF values obtained by thin-layer chromatography for a group of anilines with connectivity indices proposed by Kier and Hall has been studied. Using multivariable regression the corresponding connectivity functions, selected for their respective correlation coefficients, standard deviations, Snedecor's F and Student's t were obtained. Regression analysis of the connectivity functions gives a correct prediction of the experimental elution sequence for this group of substances on silica gel stationary phases and various mobile phases of different polarity. The corresponding random and stability studies of the different prediction models selected were carr…
Discrimination and Molecular Design of New Theoretical Hypolipaemic Agents Using the Molecular Connectivity Functions
2000
The molecular topology model and discriminant analysis have been applied to the prediction and QSAR interpretation of some pharmacological properties of hypolipaemic drugs using multivariable regression equations with their statistical parameters. Regression analysis showed that the molecular topology model predicts these properties. The corresponding stability (cross-validation) studies done on the selected prediction models confirmed the goodness of the fits. The method used for hypolipaemic activity selection was a linear discriminant analysis (LDA). We make use of the pharmacological distribution diagrams (PDDs) as a visualizing technique for the identification and design of new hypolip…
Setpoints compensation in industrial processes via multirate output feedback control
2013
This paper investigates the setpoints compensation for a class of complex industrial processes. Plants at the device layer are controlled by the local regulation controllers, and a multirate output feedback control approach for setpoint compensation is proposed such that the subsystems can reach the dynamically changed setpoints and the given economic objective can also be tracked via certain economic performance index (EPI). First, a sampled-data multivariable direct output feedback proportional integral (PI) controller is designed to regulate the performance of the subsystems. Second, the outputs and control inputs of the plants at the device layer are sampled at operation layer sampling …
Nonlinear fuzzy control of a fed-batch reactor for penicillin production
2012
Abstract The process of penicillin production is characterized by nonlinearities and parameter uncertainties that make it difficult to control. In the paper the development and testing of a multivariable fuzzy control system that makes use of type-2 fuzzy sets for the control of pH and temperature are described. The performance of the type-2 fuzzy logic control system (T2FLCS) is compared by simulation with that of a type-1 fuzzy logic control system (T1FLCS) and that of a control system with traditional proportional-integral-derivative (PID) controllers proposed in the literature. The fuzzy controllers are optimized using an ANFIS algorithm. The best results are obtained with the T2FLCS pa…
Cluster-Localized Sparse Logistic Regression for SNP Data
2012
The task of analyzing high-dimensional single nucleotide polymorphism (SNP) data in a case-control design using multivariable techniques has only recently been tackled. While many available approaches investigate only main effects in a high-dimensional setting, we propose a more flexible technique, cluster-localized regression (CLR), based on localized logistic regression models, that allows different SNPs to have an effect for different groups of individuals. Separate multivariable regression models are fitted for the different groups of individuals by incorporating weights into componentwise boosting, which provides simultaneous variable selection, hence sparse fits. For model fitting, th…
Tailoring sparse multivariable regression techniques for prognostic single-nucleotide polymorphism signatures.
2011
When seeking prognostic information for patients, modern technologies provide a huge amount of genomic measurements as a starting point. For single-nucleotide polymorphisms (SNPs), there may be more than one million covariates that need to be simultaneously considered with respect to a clinical endpoint. Although the underlying biological problem cannot be solved on the basis of clinical cohorts of only modest size, some important SNPs might still be identified. Sparse multivariable regression techniques have recently become available for automatically identifying prognostic molecular signatures that comprise relatively few covariates and provide reasonable prediction performance. For illus…
Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous…
2012
In observational studies, many continuous or categorical covariates may be related to an outcome. Various spline-based procedures or the multivariable fractional polynomial (MFP) procedure can be used to identify important variables and functional forms for continuous covariates. This is the main aim of an explanatory model, as opposed to a model only for prediction. The type of analysis often guides the complexity of the final model. Spline-based procedures and MFP have tuning parameters for choosing the required complexity. To compare model selection approaches, we perform a simulation study in the linear regression context based on a data structure intended to reflect realistic biomedica…
On stability issues in deriving multivariable regression models
2014
In many areas of science where empirical data are analyzed, a task is often to identify important variables with influence on an outcome. Most often this is done by using a variable selection strategy in the context of a multivariable regression model. Using a study on ozone effects in children (n = 496, 24 covariates), we will discuss aspects relevant for deriving a suitable model. With an emphasis on model stability, we will explore and illustrate differences between predictive models and explanatory models, the key role of stopping criteria, and the value of bootstrap resampling (with and without replacement). Bootstrap resampling will be used to assess variable selection stability, to d…