Description Usage Arguments Value References Examples
This function develops an one-step ahead prediction algorithm based on Poisson dynamic generalized linear model (DGLM) for the count of crime in Manaus.
1 2 |
x |
A data frame containig the following columns:LAT,LONG,DATA,DIA.SEMANA, HORA,PERIODO,Crime. |
type |
Character string giving the type of crime to make the predictions. In this version only "ROUBO" is available. |
nMap |
Number of maps to check the quality of predictions. |
delta |
Discount factor. |
by1 |
Character string specifying the periodicity of the counts. In this version only "week" is available. |
k0 |
Number of periods to use as prior information. |
UsePrior |
Default is |
m0 |
First posterior moment at t-1. |
c0 |
Second posterior moment at t-1. |
A map that provides predictions of crime intensity and the mean square error.
Harrison, Jeff, and Mike West. Bayesian forecasting & dynamic models. New York: Springer, 1999.
TRIANTAFYLLOPOULOS, K. Dynamic z generalized linear models for non-Gaussian time series forecasting. arXiv preprint arXiv:0802.0219, 2008.
1 2 | data(crimes1415)
predCrimMao(crimes1415,type="ROUBO",by1="week",nMap=2)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.