Regularise and smooth an irregular timeseries.

Usage

SmoothIrregular(df, time.var, value.var, tau_smooth, d_t = NULL)

Arguments

df: A dataframe with columns of ages and values
time.var: A quoted string giving the name of the age column
value.var: A quoted string giving the name of the value column
tau_smooth: Width of the boxcar / uniform smoothing window
d_t: Difference between time steps of new regular time series

Examples

set.seed(20191205)
n <- 100
dat <- data.frame(time = sort(runif(n, 1, 1e04)),
 value = arima.sim(list(ar = 0.9), n = n)
 )
plot(dat, type = "b")
dat.smoothed <- SmoothIrregular(dat, "time", "value", tau_smooth = 500)
dat.smoothed.2 <- SmoothIrregular(dat, "time", "value", tau_smooth = 500,
 d_t = 500)
lines(mean.value~age, data = dat.smoothed, col = "Red")
lines(mean.value~age, data = dat.smoothed.2, col = "Blue")

head(dat.smoothed)
#>        age mean.value n  mean.d_t tau_smooth
#> 1 194.0280   1.971426 1 500.00000        500
#> 2 291.0419   1.751131 2 250.00000        500
#> 3 388.0559   1.976105 4 125.00000        500
#> 4 485.0699   1.976105 4 125.00000        500
#> 5 582.0839   2.221144 4 125.00000        500
#> 6 679.0978   1.843450 6  83.33333        500