Smooth data in 5-year age groups.

smooth_age_5_mav(Value, Age, OAG = TRUE, n = 3, tails = FALSE)

Value | numeric vector of (presumably) counts in 5-year age groups. |
---|---|

Age | integer vector of age group lower bounds. |

OAG | logical. Whether or not the top age group is open. Default |

n | integer. The width of the moving average. Default 3 intervals (x-5 to x+9). |

tails | logical. If tails is |

numeric vector of smoothed counts in 5-year age groups.

This function calls `smooth_age_5_zigzag_inner()`

, but prepares data in a way consistent with other methods called by `smooth_age_5()`

. It is probably preferable to call `zigzag()`

from the top level, or else call this method from `agesmth()`

for more control over tail imputations.

If tails is set to `FALSE`

, this function calls `mav()`

, which itself relies on the more general `ma()`

. We lose the lowest and highest ages with this method, unless `n=1`

, in which case data is returned in the original 5-year age groups. The total population count is not constrained to sum to the original total.

If tails is `TRUE`

, the same results are expected but the tails are
filled in using a cascading method.

Age <- c(0,1,seq(5,90,by=5)) # defaults ns <- sapply(1:5,smooth_age_5_mav,Value=dth5_zigzag,Age=Age,OAG=TRUE) cols <- paste0(gray(seq(.8,0,length=5)),"A0") lwds <- seq(4,1,length=5) if (FALSE) { plot(Age, dth5_zigzag,pch=16) matplot(as.integer(rownames(ns)),ns,type='l', col = cols, lty = 1, add = TRUE, lwd = lwds) legend("topright", col = cols, lty = 1, lwd = lwds, legend = paste("n =",1:5)) }