<--- Back to Details
First PageDocument Content
Signal processing / Time series analysis / Ergodic theory / Stationary process / Autocovariance / Covariance function / Time series / Ergodicity / Autocorrelation / Statistics / Covariance and correlation / Stochastic processes
Date: 2011-01-26 13:26:58
Signal processing
Time series analysis
Ergodic theory
Stationary process
Autocovariance
Covariance function
Time series
Ergodicity
Autocorrelation
Statistics
Covariance and correlation
Stochastic processes

Add to Reading List

Source URL: economia.unipv.it

Download Document from Source Website

File Size: 122,49 KB

Share Document on Facebook

Similar Documents

A Process over all Stationary Covariance Kernels Andrew Gordon Wilson June 9, 2012 Abstract I define a process over all stationary covariance kernels. I show how one might be able to perform inference that scales as O(nm

DocID: 1sZ1U - View Document

Six Results from the Frequency Domain • Suppose {Yt} is a covariance stationary process with no deterministic component. By Wold’s Decomposition Theorem (see, e.g., Sargent, Macroeconomic Theory, chapter XI, section

DocID: 1sr4m - View Document

Graph theory / Mathematics / Computational complexity theory / Operations research / Combinatorial optimization / Routing algorithms / Search algorithms / Edsger W. Dijkstra / Travelling salesman problem / A* search algorithm / Flow network / Tree traversal

Approximation bounds for Black Hole Search problems? Ralf Klasing?? , Euripides Markou? ? ? , Tomasz Radzik† , Fabiano Sarracco‡ Abstract. A black hole is a highly harmful stationary process residing in a node of a n

DocID: 1rjuk - View Document

Mathematical analysis / Probability / Stochastic processes / Stochastic differential equations / Markov models / Signal processing / Stationary process / Derivative / Spectrum / Normal distribution / OrnsteinUhlenbeck process / Markov chain

STATIONARY TANGENT: THE DISCRETE AND NON-SMOOTH CASE U. KEICH Abstract. In [5] we define a stationary tangent process, or a locally optimal stationary approximation, to a real non-stationary smooth Gaussian process. Thi

DocID: 1r1JJ - View Document

Covariance and correlation / Probability theory / Stochastic processes / Data / Mathematical analysis / Spatial data analysis / Signal processing / Stationary process / Correlation function / Van Lieshout / Correlation and dependence / Point process

Ann Inst Stat Math:905–928 DOIs10463z Summary statistics for inhomogeneous marked point processes O. Cronie · M. N. M. van Lieshout

DocID: 1qV54 - View Document