Anisotropic Scaling Of Random Fields With Long-range Dependence: Scaling Limits Of Random Fields With Applications
Regular price
€102.99
14 days return policy
Shipping & Delivery
A01=Donatas Surgailis
Anisotropic Scaling Limit
Appell Polynomials
Author_Donatas Surgailis
Category=PBWL
Contemporaneous Aggregation
Dependence Axis
Edge Effect
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
forthcoming
Fractional Brownian Motion
Fractional Brownian Sheet
Fractional Integration
Fractional Random Field
Gaussian Random Field
Generalized Homogeneous Function
Hermite Polynomials
Hurst Indices
Infinite Source Poisson Process
Levy Random Measure
Local Self-Similarity
Long-Range Dependence
Matern Random Field
Multi Self-Similar Random Field
Multiple Ito-Wiener Integral
Negative Dependence
Network Traffic
ONOFF Process
Ornstein-Uhlenbeck Intermediate Process
Random Coefficient AR(1) Process
Random Field
Rectangent Random Field
Rectangular Increment
Regenerative Process
Renewal Process
Renewal-Reward Process
Scaling Diagram
Scaling Transition
Shot-Noise Process
Spectral Density
Stable Random Field
Stochastic Integral
Sub-Gaussian Process
Tangent Random Field
Telecom Process
Unbalanced Scaling Limit
Well-Balanced Scaling Limit
Product details
- ISBN 9789811249419
- Publication Date: 29 Jul 2026
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
Secure
checkout
Fast Shipping
Easy returns
Anisotropic Scaling of Random Fields with Long-Range Dependence is primarily interested in two questions: are there scaling limits for all γ>0 ratios? And if so, what are they? By introducing the concept of a scaling transition and discussing its existence for Gaussian models, moving-average models, and their subordinated planar models, the very cutting-edge of research and theory within scaling transition is explored, interrogated, and understood.If a scaling parameter tends to zero or infinity (infinite scaling), this can lead to a limit which is self-similar and much simpler than the original object. In the case of a random field indexed by a two-dimensional, both types of scaling can be anisotropic — meaning that the horizontal and vertical axes are scaled at different rates determined by the ratio γ>0 of the scaling exponents along the axes. Within this text, a wide class of linear and nonlinear random fields are analysed through the critically underdiscussed concept of a scaling transition. A central engagement of this research involves joint temporal and contemporaneous aggregation of spatio-temporal models with long-range dependence in applied sciences (telecommunications and econometrics) and the scaling transition arising when the number of spatial components and time scale increase at different rates.This book is intended for advanced graduate and PhD students, as well as researchers and practitioners in the fields of stochastic processes, spatial statistics, econometrics and telecommunications, although researchers working in applied sciences such as geophysics will also find value in its study.
