Bøker i Lecture Notes in Statistics-serien

This textbook provides a self-contained presentation of the theory and models of time series analysis. Putting an emphasis on weakly stationary processes and linear dynamic models, it describes the basic concepts, ideas, methods and results in a mathematically well-founded form and includes numerous examples and exercises. The first part presents the theory of weakly stationary processes in time and frequency domain, including prediction and filtering. The second part deals with multivariate AR, ARMA and state space models, which are the most important model classes for stationary processes, and addresses the structure of AR, ARMA and state space systems, Yule-Walker equations, factorization of rational spectral densities and Kalman filtering. Finally, there is a discussion of Granger causality, linear dynamic factor models and (G)ARCH models. The book provides a solid basis for advanced mathematics students and researchers in fields such as data-driven modeling, forecasting and filtering, which are important in statistics, control engineering, financial mathematics, econometrics and signal processing, among other subjects.

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...

In these cases, both the exact quantiles and the exact p-values of the likelihood ratio tests can be computed quickly and efficiently.The test statistics in question range from common ones, such as those used to test e.g.

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.

These nine papers cover three different areas for longitudinal data analysis, four dealing with longitudinal data subject to measurement errors, four on incomplete longitudinal data analysis, and the last one for inferences for longitudinal data subject to outliers.

This proceedings volume contains eight selected papers thatwere presented in the International Symposium in Statistics (ISS) 2015 OnAdvances in Parametric and Semi-parametric Analysis of Multivariate, TimeSeries, Spatial-temporal, and Familial-longitudinal Data, held in St. John's,Canada from July 6 to 8, 2015.

This volume gathers papers originally presented at the 3rd Workshop on Branching Processes and their Applications (WBPA15), which was held from 7 to 10 April 2015 in Badajoz, Spain (http://branching.unex.es/wbpa15/index.htm).

Stochastic Orders in Reliability and Risk Management is composed of 19 contributions on the theory of stochastic orders, stochastic comparison of order statistics, stochastic orders in reliability and risk analysis, and applications.

The chapters in this volume stress the need for advances in theoretical understanding to go hand-in-hand with the widespread practical application of forecasting in industry.

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 contains papers based on these presentations, as well as vignettes provided by Paul Holland before each section.The papers in this book attest to how Paul Holland's pioneering ideas influenced and continue to influence several fields such as social networks, causal inference, item response theory, equating, and DIF.

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.

The product of a high-flying summer school in Paris in 2009, this volume synthesises the state of the art on ill-posed statistical inverse problems and high-dimensional estimation and explores the ways these techniques can be applied to economics.

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.

This revised book presents theoretical results relevant to Edgeworth and saddlepoint expansions to densities and distribution functions. Variants on these expansions, including much of modern likelihood theory, are discussed and applications to lattice distributions are extensively treated.

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.