crime_W: Network matrix for Chicago crime dataset
In PNAR: Poisson Network Autoregressive Models
crime_W R Documentation
Network matrix for Chicago crime dataset
Description
Non-negative row-normized adjacency matrix describing the network structure
between Chicago census blocks.
Usage
crime_W
Format
A matrix with 552 rows and 552 columns.
Source
Clark and Dixon (2021), available at https://github.com/nick3703/Chicago-Data.
References
Clark, N. J. and P. M. Dixon (2021). A class of spatially correlated
self-exciting statistical models. Spatial Statistics, 43, 1–18.
See Also
crime, lin_estimnarpq, log_lin_estimnarpq
Examples
data(crime)
data(crime_W)
mod1 <- lin_estimnarpq(crime, crime_W, p = 1)
mod2 <- log_lin_estimnarpq(crime, crime_W, p = 1)
PNAR documentation built on Sept. 12, 2024, 7:30 a.m.
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| crime_W | R Documentation |
Network matrix for Chicago crime dataset
Description
Non-negative row-normized adjacency matrix describing the network structure between Chicago census blocks.
Usage
crime_WFormat
A matrix with 552 rows and 552 columns.
Source
Clark and Dixon (2021), available at https://github.com/nick3703/Chicago-Data.
References
Clark, N. J. and P. M. Dixon (2021). A class of spatially correlated self-exciting statistical models. Spatial Statistics, 43, 1–18.
See Also
crime, lin_estimnarpq, log_lin_estimnarpq
Examples
data(crime)
data(crime_W)
mod1 <- lin_estimnarpq(crime, crime_W, p = 1)
mod2 <- log_lin_estimnarpq(crime, crime_W, p = 1)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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