'Point process' presentation slideshows

Applications of space-time point processes in wildfire forecasting

Applications of space-time point processes in wildfire forecasting. Background Problems with existing models (BI) A separable point process model Testing separability Alarm rates & other basic assessment techniques.

671 views • 58 slides

Applications of space-time point processes in wildfire forecasting

Applications of space-time point processes in wildfire forecasting. Background Problems with existing models (BI) A separable point process model Testing separability Alarm rates & other basic assessment techniques.

649 views • 58 slides

Probabilistic Risk Modelling at the Wildland Urban Interface: the 2003 Cedar Fire, II

Probabilistic Risk Modelling at the Wildland Urban Interface: the 2003 Cedar Fire, II David R. Brillinger, Statistics UC Berkeley (brill@stat.berkeley.edu, www.stat.berkeley.edu/~brill) Benjamin Scott Autrey, PopularMedia Inc. (Sequoia Ventures) (benjamin.scott@gmail.com)

687 views • 53 slides

Tracking in High Target Densities Using a First-Order Multitarget Moment Density

Tracking in High Target Densities Using a First-Order Multitarget Moment Density. Ronald Mahler, Ph.D. Lockheed Martin NE&SS Tactical Systems Eagan, Minnesota, USA 651-456-4819 / ronald.p.mahler@lmco.com IMA Industrial Seminar Series, University of Minnesota October 4, 2002. Problem.

552 views • 39 slides

637 views • 39 slides

An Introduction to Point Processes

Definitions & examples Conditional intensity & Papangelou intensity Models a) Renewal processes b) Poisson processes c) Cluster models d) Inhibition models. An Introduction to Point Processes. Point pattern : a collection of points in some space.

535 views • 37 slides

Use of A( ?,? ). bandpass filtering

417 views • 35 slides

Throughput Improvement in Ad hoc networks using the Channel MAC

Throughput Improvement in Ad hoc networks using the Channel MAC. Manzur Ashraf ITR, University of South Australia. Contents. Motivation: opportunistic communication The Channel MAC protocol Analytical model Discrete event simulation Challenges: Practical implementation.

527 views • 34 slides

The Empirical FT continued .

The Empirical FT continued. What is the large sample distribution of the EFT?. The complex normal. Theorem. Suppose p.p. N is stationary mixing, then. Proof. Write. Evaluate first and second-order cumulants Bound higher cumulants Normal is determined by its moments. Consider.

367 views • 31 slides

Second order stationary p.p. dN(t) = ? exp{ i ? t} dZ N ( ? ) dt Kolmogorov

Second order stationary p.p. dN(t) = ? exp{ i ? t} dZ N ( ? ) dt Kolmogorov N(t) = Power spectrum cov{dZ N ( ? ), dZ N ( ? } = ? ( ? - ? ) f NN d ? d ? remember Z complex-valued Bivariate p.p. process {M,N} Coherency

381 views • 30 slides

The Empirical FT .

The Empirical FT. What is the large sample distribution of the EFT?. The complex normal. Theorem. Suppose X is stationary mixing, then. Proof. Write. Evaluate first and second-order cumulants Bound higher cumulants Normal is determined by its moments. Consider. Comments .

354 views • 29 slides

Statistical Multiplexing

Statistical Multiplexing. 1 ? : ? ? ? ? ? ? ? ? ?. ??. Introduction Superposition of ATM traffics - Fundamental limit Theorem - Superposition of Poisson, Renewal, Point process - Limit Theorem ? ?? ?? Theoretical Apporach of Superposition - PDF

426 views • 27 slides

331 views • 23 slides

338 views • 23 slides

Maps, images, spatial displays - Always look at the data

Maps, images, spatial displays - Always look at the data responses, "Y" explanatories, "X". Y + X. Saskatchewan, Canada responses,"Y" explanatories,"X" polygon(), text(), library(maps),. Examples from the news Costa Concordia - Giglio.

287 views • 20 slides

Improved characterization of neural and behavioral response properties using point-process state-space framework

Improved characterization of neural and behavioral response properties using point-process state-space framework. Anna Alexandra Dreyer. Harvard-MIT Division of Health Sciences and Technology Speech and Hearing Bioscience and Technology Program Neurostatistics Research Laboratory, MIT

399 views • 19 slides

Group 2

301 views • 16 slides

Individual needs within the health and social care sectors

Individual needs within the health and social care sectors. Hazards in health and social care environments. What is the difference between a hazard and a risk?. Hazard is the object that could potentially hurt someone Risk is the harm it could do.

356 views • 15 slides

Dynamic Spatial Mixture Modelling and its Application in Cell Tracking - Work in Progress -

Dynamic Spatial Mixture Modelling and its Application in Cell Tracking - Work in Progress -. Chunlin Ji & Mike West Department of Statistical Sciences, Duke University SMC Mid-Program Workshop February 19, 2009. Outline. Spatial Inhomogeneous Point Process

236 views • 15 slides

Detection and Analysis of Impulse Point Sequences on Correlated Disturbance Phone

Detection and Analysis of Impulse Point Sequences on Correlated Disturbance Phone. G. Filaretov , A. Avshalumov Moscow Power Engineering Institute, Moscow Research Institute of Cybernetic Medicine. Setting of Problem Let the observable discrete process z is the sum: z = x + i.

275 views • 13 slides