Books in the Lecture Notes in Statistics series

1.1 Rationale.- 1.2 An Overview.- Soil Acidification: Fundamental Concepts.- The Sulfur System.- 3.1 The Sulfate Cycle.- 3.2 Sulfate Adsorption.- 3.3 The Biotic Component.- 3.4 Summary.- The Nitrogen System.- 4.1 Acid-Base Relationships of the Nitrogen Cycle.- 4.2 Acid-Base Relationships of Nitrogen Inputs.- 4.3 Ecosystem Effects.- Soil-Solution Interactions.- 5.1 Role of Anions.- 5.2 Ion Equilibria Model.- 5.3 Conceptualizing the Model.- 5.4 Solution Concentration Effects.- 5.5 Cation Removal, ?M/?H.- 5.6 Complexes and Precipitates.- 5.7 Organic Anions.- 5.8 Summary.- Forest Element Cycling.- 6.1 Definition of Terms.- 6.2 Effects of Acid Deposition on Base Cation Flux.- 6.3 Cation Nutrient Effects.- The Aquatic Interface.- 7.1 Alkalinity Concepts.- 7.2 Alkalinity in Soil Solution.- 7.3 Naturally Acid Waters.- 7.4 Sensitivity to Water Acidification.- 7.5 Capacity versus Intensity.- Soil Sensitivity.- Base Cation Depletion.- Sensitivity to pH Changes.- Sensitivity to Aluminum Mobilization.- Summary.- Conclusion.- 9.1 Summary.- 9.2 Concepts in Transition.- References.- Appendix: Model Documentation.- A.1 Model Description.- A.2 Program Operation.- A.3 Program Documentation.- A.4 Program Listings.

I. Additives Which Modify Physical Properties.- 1 Plasticizers.- 1.1 Thermodynamic Basis of Macromolecular Mixtures.- 1.1.1 Solubility of Polymers in Solvents.- 1.1.2 Flory-Huggins Interaction Parameter.- 1.1.3 Solubility Parameter.- 1.1.4 Phase Separation Phenomena.- 1.2 Reversible Gelation.- 1.3 Theory of Plasticization.- 1.3.1 Effect of Plasticizers on Thermal Mechanical Deformation of Rigid Polymeric Chains.- 1.3.2 Effect of Plasticizers on Tb and Tg Values.- 1.3.3 The Free Volume in Amorphous Polymers.- 1.3.4 Primary and Secondary Plasticizers.- 1.4. Classification of Plasticizers.- 1.4.1 Polar Aromatic and Polar Aliphatic Plasticizers.- 1.4.2 Characteristics of Plasticizers According to Their Chemical Structure.- 1.5. Plasticizer Anomalies and Antiplasticization.- 1.6. Loss of Plasticizers.- References.- 2 Lubricants and Mold-Release Agents.- 2.1 Lubricants.- 2.1.1 Principles of Their Action.- 2.1.2 Classification of PVC Lubricants According to Their Specific Action.- 2.1.3 Classification of PVC Lubricants According to Their Chemical Structure.- 2.1.4 Lubricants for Polyolefins.- 2.1.5 Basic Properties Necessary for Lubricants.- 2.2 Mold-Release Agents.- 2.2.1 Principles of Action.- 2.2.2 Some Examples of Mold-Release Agents.- References.- 3 Macromolecular Modifiers.- 3.1 Introduction.- 3.2 Homogenization of Polymer-Polymer Systems.- 3.3 Two-Phase Microheterogeneous Polymer-Polymer Systems.- 3.3.1 Effect of Glassy Polymer Matrix Phase on Impact Strength.- 3.3.2 Effect of Rubbery Phase Dispersed in Glassy Matrix on Impact Strength.- 3.3.3 Theory on Toughness of Microheterogeneous Two-Phase Polymer-Polymer Blends.- 3.4 Impact Modifiers for Glassy Polymers.- 3.4.1 Chlorinated Polyethylene (CPE).- 3.4.2 Ethylene-(Vinyl Acetate) Copolymers (EVA).- 3.4.3 Acrylic and Methacrylic Elastomers and MBS and ABS Terpolymers.- 3.4.4 Rubbers.- 3.5 Macromolecular Modifiers Used as Polymer Processing Aids.- References.- 4 Reinforcing Fillers, Reinforcing Agents, and Coupling Agents.- 4.1 Fillers.- 4.1.1 General Characteristics of Fillers and Composites.- 4.1.2 Fillers for Thermosetting Resins.- 4.1.3 Fillers for Plastomers.- 4.1.3.1 Polymer Reinforcement Factors.- 4.1.3.2 Classification of Fillers for Plastomers According to Their Reinforcement Activity.- 4.2 Reinforcing Agents for Laminates.- 4.2.1 Effect of Fillers or Reinforcing Agents on Basic Physical Properties of Composites.- 4.3 The Different Types of Fillers and Reinforcing Agents.- 4.3.1 Glass Fillers and Reinforcing Agents.- 4.3.1.1 Glass Fibers.- 4.3.1.2 Glass Microspheres.- 4.3.1.3 Glass Flakes.- 4.3.2 Fillers and Reinforcing Agents Made of Other Materials.- 4.3.2.1 Fibrous and Flaky Fillers and Fibrous Reinforcing Agents.- 4.3.2.2 Whiskers, Microfibers, and Powdered Fillers.- 4.3.3 Effect of Content and Size of Fillers on Composite Properties.- 4.4 Coupling Agents.- 4.4.1 Silane Coupling Agents.- 4.4.1.1 Action Mechanism.- 4.4.2 Organotitanate Coupling Agents.- 4.4.2.1 Action Mechanism.- 4.4.3 Other Types of Coupling Agents.- 4.4.4 Application Modes for Coupling Agents.- 4.4.5 Recommendations on the Use of Fillers and Filling Methods.- References.- 5 Colorants and Brightening Agents.- 5.1 Colorants.- 5.1.1 Inorganic Pigments.- 5.1.2 Organic Pigments.- 5.1.3 Criteria for Selection of Pigments.- 5.2 Brightening Agents.- 5.3 Methods Used for the Coloration of Plastics.- 5.3.1 Some Examples of Methods Used for the Coloration of Most Important Plastics.- References.- 6 Chemical and Physical Blowing Agents.- 6.1 Chemical Blowing Agents.- 6.1.1 Inorganic Agents.- 6.1.2 Organic Agents.- 6.1.2.1 Characteristics.- 6.1.3 Factors Acting on Blowing.- 6.2 Physical Blowing Agents.- References.- 7 Antistatic Agents.- 7.1 Introduction.- 7.2 Efficiency and Mechanism of Antistatic Agent Action.- 7.3 The Use of Antistatic Agents.- 7.3.1 Antistatic Agents Containing Nitrogen.- 7.3.2 Antistatic Agents Containing Phosphorus.- 7.3.3 Antistatic Agents Containing Sulfur.- 7.3.4 Betaine-Type Antist...

This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions.

The models studied are fractional Brownian motions and processes that derive from them through stochastic differential equations.Concerning the proofs of the limit theorems, the "Fourth Moment Theorem" is systematically used, as it produces rapid and helpful proofs that can serve as models for the future.

Dihedral Fourier Analysis introduces the theory and applications necessary to study experimental data indexed by, or associated with, the points in a dihedral symmetry orbit. This book looks at experimental data and analytical models indexed by certain dihedral rotations and reversals realized as vector fields.

Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. This book is divided into two main parts: Part I - "Surveys" contains 11 chapters that provide an up-to-date account of essential aspects of copula models.

From the reviews: "In this Lecture Note volume the author describes his differential-geometric approach to parametrical statistical problems summarizing the results he had published in a series of papers in the last five years.

This book covers a wide range of topics in both discrete and continuous optimal designs. The topics discussed include designs for regression models, covariates models, models with trend effects, and models with competition effects.

A title that arises from the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place March 2010. It details developments, methods and applications in spatial statistics and related areas.

Their niche of mathematics is the abstract pattern of reproduction, sets of individuals changing size and composition through their members reproducing; Branching is a clean and beautiful mathematical pattern, with an intellectually challenging intrinsic structure, and it pervades the phenomena it underlies.

Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data.

Random Effect and Latent Variable Model Selection In recent years, there has been a dramatic increase in the collection of multivariate and correlated data in a wide variety of ?elds.

Covering statistical analysis on the two special manifolds, the Stiefel manifold and the Grassmann manifold, this book is designed as a reference for both theoretical and applied statisticians.

This book gives a comprehensive introduction to exponential family nonlinear models, which are the natural extension of generalized linear models and normal nonlinear regression models. The differential geometric framework is presented for these models and the geometric methods are widely used in this book.

This concise, easy-to-follow book stimulates interest and develops proficiency in statistical analysis.

This book outlines and demonstrates problems with the use of the HP filter, and proposes an alternative strategy for inferring cyclical behavior from a time series featuring seasonal, trend, cyclical and noise components.

The main subject of this book is the estimation and forecasting of continuous time processes. It leads to a development of the theory of linear processes in function spaces. Mathematical tools are presented, as well as autoregressive processes in Hilbert and Banach spaces and general linear processes and statistical prediction.

This book will be of interest to mathematical statisticians and biometricians interested in block designs. After presenting the general theory of analysis based on the randomization model in Part I, the constructional and combinatorial properties of design are described in Part II.

By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Statisticians, mathematicians, and engineers will find the book useful as a research reference.

Robust Bayesian analysis aims at overcoming the traditional objection to Bayesian analysis of its dependence on subjective inputs, mainly the prior and the loss.

This collection of papers provides an up to date treatment of item response theory, an important topic in educational testing.

In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account.

These notes represent our summary of much of the recent research that has been done in recent years on approximations and bounds that have been developed for compound distributions and related quantities which are of interest in insurance and other areas of application in applied probability.

Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited.