dlm_close {BayesMortalityPlus} | R Documentation |

This function receives an object of the class `DLM`

fitted by the dlm() function
and fits a closing method to expand the life tables dataset to a maximum age argument inputed
by the user.
There are three closing methods available: 'linear', 'gompertz' and 'plateau'.

```
dlm_close(fit, method = c("linear", "gompertz", "plateau"),
x0 = max(fit$info$ages), max_age = 120, k = 7,
weights = seq(from = 0, to = 1, length.out = k),
new_data = NULL)
```

`fit` |
Object of the class |

`method` |
Character string specifying the closing method to be fitted, with them being: 'plateau', 'linear' or 'gompertz'. |

`x0` |
Integer with the starting age the closing method will be fitted from. Default is the last age fitted by the 'DLM' object. |

`max_age` |
Integer with the maximum age the closing method will be fitted. Default age is '120'. |

`k` |
Integer representing the size of the age-interval to be mixed with the 'linear' or 'gompertz' closing methods for a smooth graduation. If k = 0, no mixing will be made. Default: 7. |

`weights` |
Vector of weights to be applied in the mixing of the life tables. Vector's size should be equal to k. |

`new_data` |
Vector containing the log mortality rates in the period after the x0 input. This argument is necessary in the 'linear' and 'gompertz' closing methods. |

The three closing methods implemented by the function are: 1.'linear' method: Fits a linear regression starting at age x0 - k until the last age with data available 2.'gompertz' method: Used as the closing method of the 2010-2012 English Life Table No. 17, fits the Gompertz mortality law via SIR using the same available data as the 'linear' method. 3.'plateau' method: Keeps the death probability (qx) constant after the x0 argument.

Returns a `ClosedDLM`

class object with the predictive chains of the death probability
(qx) from first fitted age to max_age argument, the data information utilized by the function and the
closing method chosen.

Dodd, Erengul, Forster, Jonathan, Bijak, Jakub, & Smith, Peter 2018. “Smoothing mortality data: the English life table, 2010-12.” *Journal of the Royal Statistical Society: Series A (Statistics in Society)*, 181(3), 717-735.

`fitted.DLM()`

, `plot.DLM()`

, `print.DLM()`

and `summary.DLM()`

for `ClosedDLM`

methods to native R functions `fitted()`

,
`plot()`

, `print()`

and `summary()`

.

`expectancy.DLM()`

and `Heatmap.DLM()`

for `ClosedDLM`

methods to compute and visualise the truncated life expectancy
via `expectancy()`

and `Heatmap()`

functions.

```
## Importing mortality data from the USA available on the Human Mortality Database (HMD):
data(USA)
## Selecting the exposure and the death count of the year 2010, ranging from 0 to 90 years old:
USA2010 = USA[USA$Year == 2010,]
x = 0:100
Ex = USA2010$Ex.Male[x+1]
Dx = USA2010$Dx.Male[x+1]
y <- log(Dx/Ex)
fit <- dlm(y, M = 100, bn = 20, thin = 1)
## Applying the closing function with different methods:
close1 = dlm_close(fit, method = "plateau")
### Getting new data for the linear and gompertz methods:::
x2 = 101:110
Ex2 = USA2010$Ex.Male[x2+1]
Dx2 = USA2010$Dx.Male[x2+1]
y2 <- log(Dx2/Ex2)
close2 = dlm_close(fit, method = "linear",
new_data = y2)
#### Using the other functions available in the package with the 'ClosedDLM' object:
## qx estimation (See "?fitted" in the BayesMortalityPlus package for more options):
fitted(close2)
## life expectancy (See "?expectancy.DLM" for more options)
expectancy(close2, age = seq(0,120,by=20), graph = FALSE)
## plotting (See "?plot" in the BayesMortalityPlus package for more options):
plot(list(close1, close2, fit),
colors = c("red4","seagreen", "blue"),
labels = c("Plateau method","Linear method", "DLM fitted"),
plotData = FALSE)
```

[Package *BayesMortalityPlus* version 0.1.1 Index]