Description Usage Arguments Details Value References Examples

Provides methods for the generic function `residuals`

.

1 2 3 4 |

`object` |
an object with class |

`...` |
other arguments. |

Let *ti* be the times of the observed events. Then the transformed times are defined as

*
tau_i = integral_0^{ti} of {lambda_g(t|Ht) dt}.
*

If the proposed point process model is correct, then the transformed time points will form a stationary Poisson process with rate parameter one. A plot of transformed time points versus the cumulative number of events should then roughly follow the straight line *y = x*. Significant departures from this line indicate a weakness in the model. Further details can be found in Ogata (1988) and Aalen & Hoem (1978).

See Baddeley et al (2005) and Zhuang (2006) for extensions of these methodologies.

Returns a time series object with class "`ts`

" in the case of `mpp`

. In the case of `linksrm`

a list is returned with the number of components being equal to the number of regions, and with each component being a time series object.

Cited references are listed on the PtProcess manual page.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
TT <- c(0, 1000)
bvalue <- 1
params <- c(-2.5, 0.01, 0.8, bvalue*log(10))
x <- mpp(data=NULL,
gif=srm_gif,
marks=list(NULL, rexp_mark),
params=params,
gmap=expression(params[1:3]),
mmap=expression(params[4]),
TT=TT)
x <- simulate(x, seed=5)
tau <- residuals(x)
plot(tau, ylab="Transformed Time", xlab="Event Number")
abline(a=0, b=1, lty=2, col="red")
# represent as a cusum
plot(tau - 1:length(tau), ylab="Cusum of Transformed Time", xlab="Event Number")
abline(h=0, lty=2, col="red")
``` |

PtProcess documentation built on Nov. 17, 2017, 7:12 a.m.

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