Skip to contents

Derive a set of knot points for a GAM from data

Source: R/estimator-gam.R
gam_knots.Rd

At the moment this does nothing sophisticated. An mostly equally spaced grid of knots with gaps at start and end to prevent over-fitting there. In the future this could look at the number of observations or areas where there is a lot of change to add in more knots.

Usage

gam_knots(data = i_incidence_data, window, ..., k = NULL)

Arguments

data

the function will be called with incidence data - a dataframe with columns:

  • count (positive_integer) - Positive case counts associated with the specified time frame

  • time (ggoutbreak::time_period + group_unique) - A (usually complete) set of singular observations per unit time as a `time_period`

Any grouping allowed.

window

the spacing between knots

...

currently not used

k

alternative to window, if k is given then the behaviour of the knots will be similar to the default mgcv::s(...,k=...) parameter.

Value

a vector of times (as a numeric)

Examples

gam_knots(ggoutbreak::test_poisson_rt, 14)
#> [1] 10 20 30 40 50 60 70 75
gam_knots(ggoutbreak::test_poisson_rt, k=10)
#>  [1]  0.000000  8.888889 17.777778 26.666667 35.555556 44.444444 53.333333
#>  [8] 62.222222 71.111111 80.000000