Estimates the sequential event number (SEN) quantiles for each simulated population size.

1 2 | ```
## S3 method for class 'tm'
pophistory(x, probs=seq(0, 1, 0.25))
``` |

`x` |
An object of class |

`probs` |
Probabilities passed to |

A matrix of column vectors containing the estimated SEN quantiles, with row names specifying the population size.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
# Load example dataset
data(pdm)
transitions <- full.transitions(pdm$unitary.transitions, pdm$loci)
pi <- stationary.dist(transitions)
n <- 10
mu <- 1
samples <- 10
est.res <- tm(transitions, pi, pdm$population, n, mu, samples)
# Plot minimum, median and maximum SEN as a function of population size
h <- pophistory(est.res, probs=c(0, 0.5, 1))
matplot(h, rownames(h), type="s", lty=c(3, 1, 3), col="black",
xlab="Population size", ylab="SEN")
``` |

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