entropy_k | R Documentation |

Calculate Keyfitz's entropy from a vector of age-specific survivorship
(`lx`

).

```
entropy_k(lx, trapeze = FALSE, ...)
```

`lx` |
Either a survivorship trajectory (a vector of monotonically-declining values in the interval [0,1]), or submatrix U from a matrix population model. |

`trapeze` |
A logical argument indicating whether the composite trapezoid approximation should be used for approximating the definite integral. |

`...` |
Additional variables passed to 'mpm_to_lx' if data are supplied as a matrix |

Keyfitz's life table entropy.

Note that this function may produce unexpected results if used on partial
survivorship trajectories. In addition, it is sensitive to the length of the
survivorship vector. We direct users to the function
'`shape_surv`

' which is relatively robust to these issues.

Owen R. Jones <jones@biology.sdu.dk>

Roberto Salguero-Gomez <rob.salguero@zoo.ox.ac.uk>

Keyfitz, N. 1977. Applied Mathematical Demography. New York: Wiley.

Demetrius, L., & Gundlach, V. M. 2014. Directionality theory and the entropic principle of natural selection. Entropy 16: 5428-5522.

Other life history traits:
`entropy_d()`

,
`gen_time()`

,
`life_expect_mean()`

,
`longevity()`

,
`net_repro_rate()`

,
`repro_maturity`

,
`shape_rep()`

,
`shape_surv()`

```
data(mpm1)
# derive lx trajectory, starting from stage 2
lx <- mpm_to_lx(mpm1$matU, start = 2)
# calculate Keyfitz' entropy
entropy_k(lx)
# use trapezoid approximation for definite integral
entropy_k(lx, trapeze = TRUE)
# calculate directly from the matrix
entropy_k(mpm1$matU)
```

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