Skip to Main Content
Spatial Point Patterns
book

Spatial Point Patterns

by Adrian Baddeley, Ege Rubak, Rolf Turner
November 2015
Intermediate to advanced content levelIntermediate to advanced
828 pages
33h 11m
English
Chapman and Hall/CRC
Content preview from Spatial Point Patterns
446 Spatial Point Patterns: Methodology and Applications with R
Influence for Poisson point process models
The influence of a point process model is effectively a value attached to each data point (i.e. each
point of the po int pattern to whic h the model was fitted) . It is a discrete measu re on the data points
x
i
with masses
m
i
=
1
p
Z(x
i
)I
ˆ
θ
1
Z(x
i
)
T
. (11.44)
The influence value m
i
at data point x
i
represents the change in the maximised log-likelihood that
occurs whe n the point x
i
is deleted. A relatively large value of m
i
indicates a data point with a large
influence on the fitted model.
Since the influence measure turns out to be a n atomic measure on the data ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Visualization Analysis and Design

Visualization Analysis and Design

Tamara Munzner
R in Action, Third Edition

R in Action, Third Edition

Robert I. Kabacoff

Publisher Resources

ISBN: 9781482210217