Forecasting with Exponential Smoothing The State Space Approach /

• Κύριοι συγγραφείς: Hyndman, Rob (Συγγραφέας), Koehler, Anne (Συγγραφέας), Ord, Keith (Συγγραφέας), Snyder, Ralph (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
• Σειρά: Springer Series in Statistics,
• Θέματα: Mathematics.; Probabilities.; Statistics.; Economic theory.; Probability Theory and Stochastic Processes.; Statistics for Business/Economics/Mathematical Finance/Insurance.; Economic Theory/Quantitative Economics/Mathematical Methods.; Statistical Theory and Methods.

Exponential smoothing methods have been around since the 1950s, and are the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state space models, lik...

Πίνακας περιεχομένων:

• Basic Concepts
• Getting Started
• Essentials
• Linear Innovations State Space Models
• Nonlinear and Heteroscedastic Innovations State Space Models
• Estimation of Innovations State Space Models
• Prediction Distributions and Intervals
• Selection of Models
• Further Topics
• Normalizing Seasonal Components
• Models with Regressor Variables
• Some Properties of Linear Models
• Reduced Forms and Relationships with ARIMA Models
• Linear Innovations State Space Models with Random Seed States
• Conventional State Space Models
• Time Series with Multiple Seasonal Patterns
• Nonlinear Models for Positive Data
• Models for Count Data
• Vector Exponential Smoothing
• Applications
• Inventory Control Applications
• Conditional Heteroscedasticity and Applications in Finance
• Economic Applications: The Beveridge–Nelson Decomposition.