Denton method relies on the principle of movement preservation. There exist a few variants corresponding to different definitions of movement preservation: additive first difference (AFD), proportional first difference (PFD), additive second difference (ASD), proportional second difference (PSD), etc. The default and most widely used is the Denton PFD method.
Usage
denton(
s = NULL,
t,
d = 1,
mul = TRUE,
nfreq = 4,
modified = TRUE,
conversion = c("Sum", "Average", "Last", "First", "UserDefined"),
obsposition = 1
)Arguments
- s
Preliminary series. If not NULL, it must be the same class as t.
- t
Aggregation constraint. Mandatory. it must be either an object of class ts or a numeric vector.
- d
Differencing order. 1 by default.
- mul
Multiplicative or additive benchmarking. Multiplicative by default.
- nfreq
Annual frequency of the disaggregated variable. Used if no disaggregated series is provided.
- modified
Modified (TRUE) or unmodified (FALSE) Denton. Modified by default.
- conversion
Conversion rule. Usually "Sum" or "Average". Sum by default.
- obsposition
Position of the observation in the aggregated period (only used with "UserDefined" conversion).
Examples
Y <- ts(qna_data$B1G_Y_data$B1G_FF, frequency=1, start=c(2009,1))
# denton PFD without high frequency series
y1 <- rjd3bench::denton(t=Y, nfreq=4)
# denton PFD with high frequency series
x <- y1 + rnorm(n=length(y1), mean=0, sd=10)
y2 <- rjd3bench::denton(s=x, t=Y)
# denton ASD
y3 <- rjd3bench::denton(s=x, t=Y, d=2, mul=FALSE)