04712nam 22008175 450 991029998970332120200629225450.081-322-1883-310.1007/978-81-322-1883-8(CKB)3710000000125845(EBL)1783711(OCoLC)892239518(SSID)ssj0001276922(PQKBManifestationID)11762779(PQKBTitleCode)TC0001276922(PQKBWorkID)11247035(PQKB)11492366(MiAaPQ)EBC1783711(DE-He213)978-81-322-1883-8(PPN)179766902(EXLCZ)99371000000012584520140604d2014 u| 0engur|n|---|||||txtccrNonlinear Analysis[electronic resource] Approximation Theory, Optimization and Applications /edited by Qamrul Hasan Ansari1st ed. 2014.New Delhi :Springer India :Imprint: Birkhäuser,2014.1 online resource (362 p.)Trends in Mathematics,2297-0215Description based upon print version of record.1-322-17386-9 81-322-1882-5 Includes bibliographical references at the end of each chapters and index.Chapter 1. Best Proximity Points -- Chapter 2. Semi-Continuity Properties of Metric Projections -- Chapter 3. Convergence of Slices, Geometric Aspects in Banach Spaces and Proximinality -- Chapter 4. Measures of Non compactness and Well-Posed Minimization Problems -- Chapter 5. Well-Posedness, Regularization and Viscosity Solutions of Minimization Problems -- Chapter 6. Best Approximation in Nonlinear Functional Analysis -- Chapter 7. Hierarchical Minimization Problems and Applications -- Chapter 8. Triple Hierarchical Variational Inequalities -- Chapter 9. Split Feasibility and Fixed Point Problems -- Chapter 10. Isotone Projection Cones and Nonlinear Complementarity Problems.Many of our daily-life problems can be written in the form of an optimization problem. Therefore, solution methods are needed to solve such problems. Due to the complexity of the problems, it is not always easy to find the exact solution. However, approximate solutions can be found. The theory of the best approximation is applicable in a variety of problems arising in nonlinear functional analysis and optimization. This book highlights interesting aspects of nonlinear analysis and optimization together with many applications in the areas of physical and social sciences including engineering. It is immensely helpful for young graduates and researchers who are pursuing research in this field, as it provides abundant research resources for researchers and post-doctoral fellows. This will be a valuable addition to the library of anyone who works in the field of applied mathematics, economics and engineering.Trends in Mathematics,2297-0215Mathematical analysisAnalysis (Mathematics)Approximation theoryMathematical optimizationCalculus of variationsFunctional analysisOperator theoryAnalysishttps://scigraph.springernature.com/ontologies/product-market-codes/M12007Approximations and Expansionshttps://scigraph.springernature.com/ontologies/product-market-codes/M12023Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26008Calculus of Variations and Optimal Control; Optimizationhttps://scigraph.springernature.com/ontologies/product-market-codes/M26016Functional Analysishttps://scigraph.springernature.com/ontologies/product-market-codes/M12066Operator Theoryhttps://scigraph.springernature.com/ontologies/product-market-codes/M12139Mathematical analysis.Analysis (Mathematics).Approximation theory.Mathematical optimization.Calculus of variations.Functional analysis.Operator theory.Analysis.Approximations and Expansions.Optimization.Calculus of Variations and Optimal Control; Optimization.Functional Analysis.Operator Theory.511.4Ansari Qamrul Hasanedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910299989703321Nonlinear analysis82388UNINA05414nam 2200673Ia 450 991082982610332120230422043322.01-280-25331-297866102533190-470-24805-X0-471-72611-70-471-72841-1(CKB)1000000000018992(EBL)226443(SSID)ssj0000251094(PQKBManifestationID)11227623(PQKBTitleCode)TC0000251094(PQKBWorkID)10248229(PQKB)10729694(MiAaPQ)EBC226443(OCoLC)777630157(EXLCZ)99100000000001899219990309d2000 uy 0engur|n|---|||||txtccrStatistical methods in analytical chemistry[electronic resource] /Peter C. Meier, Richard E. Zünd2nd ed.New York Wileyc20001 online resource (452 p.)Chemical analysis ;v. 153"A Wiley-Interscience publication."0-471-29363-6 Includes bibliographical references (p. 404-415) and index.Statistical Methods in Analytical Chemistry; CHEMICAL ANALYSIS; CONTENTS; PREFACE; CHEMICAL ANALYSIS SERIES; INTRODUCTION; CHAPTER 1: UNIVARIATE DATA; 1.1 Mean and Standard Deviation; 1.1.1 The Most Probable Value; 1.1.2 The Dispersion; 1.1.3 Independency of Measurements; 1.1.4 Reproducibility and Repeatibility; 1.1.5 Reporting the Results; 1.1.6 Interpreting the Results; 1.2 Distributions and the Problem of Small Numbers; 1.2.1 The Normal Distribution; 1.2.2 Student's t Distribution; 1.3 Confidence Limits; 1.3.1 Confidence Limits of the Distribution; 1.3.2 Confidence Limits of the Mean1.4 The Simulation of a Series of Measurements1.5 Testing for Deviations; 1.5.1 Examining Two Series of Measurements; 1.5.2 The t-Test; 1.5.3 Extension of the t-Test to More Than Two Series of Measurements; 1.5.4 Multiple-Range Test; 1.5.5 Outlier Tests; 1.5.6 Analysis of Variance (ANOVA); 1.6 Number of Determinations; 1.7 Width of a Distribution; 1.7.1 The F-Test; 1.7.2 Confidence Limits for a Standard Deviation; 1.7.3 Bartlett Test; 1.8 Charting a Distribution; 1.8.1 Histograms; 1.8.2 X2-Test; 1.8.3 Probability Charts; 1.8.4 Conventional Control Charts (Shewhart Charts); 1.8.5 Cumsum Charts1.9 Errors of the First and Second KindCHAPTER 2: BI- AND MULTIVARIATE DATA; 2.1 Correlation; 2.2 Linear Regression; 2.2.1 The Standard Approach; 2.2.2 Slope and Intercept; 2.2.3 Residual Variance; 2.2.4 Testing Linearity and Slope; 2.2.5 Interpolating Y(x); 2.2.6 Interpolating X(y); 2.2.7 Limit of Detection; 2.2.8 Minimizing the Costs of a Calibration; 2.2.9 Standard Addition; 2.2.10 Weighted Regression; 2.2.11 The Intersection of Two Linear Regression Lines; 2.3 Nonlinear Regression; 2.3.1 Linearization; 2.3.2 Nonlinear Regression and Modeling; 2.4 Multidimensional Data/Visualizing DataCHAPTER 3: RELATED TOPICS3.1 GMP Background: Selectivity and Interference/Linearity/Accuracy/Precision/Reliability/Economic Considerations; 3.2 Development, Qualification, and Validation; Installation Qualification, Operations Qualification, Performance Qualification/Method Development/Method Validation; 3.3 Data Treatment Scheme: Data Acquisition/Acceptance Criteria/Data Assembly and Clean-up/Data Evaluation/ Presentation of R; 3.4 Exploratory Data Analysis (EDA); 3.5 Optimization Techniques; 3.5.1 Full Factorial vs. Classical Experiments; 3.5.2 Simplex-Guided Experiments3.5.3 Optimization of the Model: Curve Fitting3.5.4 Computer Simulation; 3.5.5 Monte Carlo Technique (MCT); 3.6 Smoothing and Filtering Data/Box-Car Averaging/Moving Average/Savitzky-Golay Filtering/CUSUM; 3.7 Error Propagation and Numerical Artifacts; 3.8 Programs; CHAPTER 4: COMPLEX EXAMPLES; 4.1 To Weigh or Not to Weigh; 4.2 Nonlinear Fitting; 4.3 UV-Assay Cost Structure; 4.4 Process Validation; 4.5 Regulations and Realities; 4.6 Diffusing Vapors; 4.7 Stability a la Carte; 4.8 Secret Shampoo Switch; 4.9 Tablet Press Woes; 4.10 Sounding Out Solubility; 4.11 Exploring a Data Jungle4.12 Sifting Through Sieved SamplesThis new edition of a successful, bestselling book continues to provide you with practical information on the use of statistical methods for solving real-world problems in complex industrial environments. Complete with examples from the chemical and pharmaceutical laboratory and manufacturing areas, this thoroughly updated book clearly demonstrates how to obtain reliable results by choosing the most appropriate experimental design and data evaluation methods.Unlike other books on the subject, Statistical Methods in Analytical Chemistry, Second Edition presents and solves problems in the coChemical analysis ;v. 153.ChemometricsChemistryChemometrics.Chemistry.543.0072543/.007/2Meier Peter C.1945-1691009Zünd Richard E1691010MiAaPQMiAaPQMiAaPQBOOK9910829826103321Statistical methods in analytical chemistry4067099UNINA