rollapply {zoo}  R Documentation 
A generic function for applying a function to rolling margins of an array.
rollapply(data, ...) ## S3 method for class 'ts' rollapply(data, ...) ## S3 method for class 'zoo' rollapply(data, width, FUN, ..., by = 1, by.column = TRUE, fill = if (na.pad) NA, na.pad = FALSE, partial = FALSE, align = c("center", "left", "right")) ## Default S3 method: rollapply(data, ...) rollapplyr(..., align = "right")
data 
the data to be used (representing a series of observations). 
width 
numeric vector or list. In the simplest case this is an integer
specifying the window width which is aligned to the original sample according
to the 
FUN 
the function to be applied. 
... 
optional arguments to 
by 
calculate FUN at every 
by.column 
logical. If 
fill 
a threecomponent vector or list (recycled otherwise) providing
filling values at the left/within/to the right of the data range.
See the 
na.pad 
deprecated. Use 
partial 
logical or numeric. If 
align 
specifyies whether the index of the result
should be left or rightaligned or centered (default) compared
to the rolling window of observations. This argument is only used if

If width
is a plain numeric vector its elements are regarded as widths
to be interpreted in conjunction with align
whereas if width
is a list
its components are regarded as offsets. In the above cases if the length of
width
is 1 then width
is recycled for every by
th point.
If width
is a list its components represent integer offsets such that
the ith component of the list refers to time points at positions
i + width[[i]]
. If any of these points are below 1 or above the
length of index(data)
then FUN
is not evaluated for that
point unless partial = TRUE
and in that case only the valid
points are passed.
The rolling function can also be applied to partial windows by setting partial = TRUE
For example, if width = 3, align = "right"
then for the first point
just that point is passed to FUN
since the two points to its
left are out of range. For the same example, if partial = FALSE
then FUN
is not
invoked at all for the first two points. If partial
is a numeric then it
specifies the minimum number of offsets that must be within range. Negative
partial
is interpreted as FALSE
.
If FUN
is mean
, max
or median
and by.column
is
TRUE
and width is a plain scalar and there are no other arguments
then special purpose code is used to enhance performance.
Also in the case of mean
such special purpose code is only invoked if the
data
argument has no NA
values.
See rollmedian
for more details.
Currently, there are methods for "zoo"
and "ts"
series
and "default"
method for ordinary vectors and matrices.
rollapplyr
is a wrapper around rollapply
that uses a default
of align = "right"
.
A object of the same class as data
with the results of the rolling function.
rollmean
## rolling mean z < zoo(11:15, as.Date(31:35)) rollapply(z, 2, mean) ## nonoverlapping means z2 < zoo(rnorm(6)) rollapply(z2, 3, mean, by = 3) # means of nonoverlapping groups of 3 aggregate(z2, c(3,3,3,6,6,6), mean) # same ## optimized vs. customized versions rollapply(z2, 3, mean) # uses rollmean which is optimized for mean rollmean(z2, 3) # same rollapply(z2, 3, (mean)) # does not use rollmean ## rolling regression: ## set up multivariate zoo series with ## number of UK driver deaths and lags 1 and 12 seat < as.zoo(log(UKDriverDeaths)) time(seat) < as.yearmon(time(seat)) seat < merge(y = seat, y1 = lag(seat, k = 1), y12 = lag(seat, k = 12), all = FALSE) ## run a rolling regression with a 3year time window ## (similar to a SARIMA(1,0,0)(1,0,0)_12 fitted by OLS) rr < rollapply(seat, width = 36, FUN = function(z) coef(lm(y ~ y1 + y12, data = as.data.frame(z))), by.column = FALSE, align = "right") ## plot the changes in coefficients ## showing the shifts after the oil crisis in Oct 1973 ## and after the seatbelt legislation change in Jan 1983 plot(rr) ## different values of rule argument z < zoo(c(NA, NA, 2, 3, 4, 5, NA)) rollapply(z, 3, sum, na.rm = TRUE) rollapply(z, 3, sum, na.rm = TRUE, fill = NULL) rollapply(z, 3, sum, na.rm = TRUE, fill = NA) rollapply(z, 3, sum, na.rm = TRUE, partial = TRUE) # this will exclude time points 1 and 2 # It corresonds to align = "right", width = 3 rollapply(zoo(1:8), list(seq(2, 0)), sum) # but this will include points 1 and 2 rollapply(zoo(1:8), list(seq(2, 0)), sum, partial = 1) rollapply(zoo(1:8), list(seq(2, 0)), sum, partial = 0) # so will this rollapply(zoo(1:8), list(seq(2, 0)), sum, fill = NA) # by = 3, align = "right" L < rep(list(NULL), 8) L[seq(3, 8, 3)] < list(seq(2, 0)) str(L) rollapply(zoo(1:8), L, sum) rollapply(zoo(1:8), list(0:2), sum, fill = 1:3) rollapply(zoo(1:8), list(0:2), sum, fill = 3) L2 < rep(list((2:0)), 10) L2[5] < list(NULL) str(L2) rollapply(zoo(1:10), L2, sum, fill = "extend") rollapply(zoo(1:10), L2, sum, fill = list("extend", NULL)) rollapply(zoo(1:10), L2, sum, fill = list("extend", NA)) rollapply(zoo(1:10), L2, sum, fill = NA) rollapply(zoo(1:10), L2, sum, fill = 1:3) rollapply(zoo(1:10), L2, sum, partial = TRUE) rollapply(zoo(1:10), L2, sum, partial = TRUE, fill = 99) rollapply(zoo(1:10), list(1), sum, partial = 0) rollapply(zoo(1:10), list(1), sum, partial = TRUE) rollapply(zoo(cbind(a = 1:6, b = 11:16)), 3, rowSums, by.column = FALSE) # these two are the same rollapply(zoo(cbind(a = 1:6, b = 11:16)), 3, sum) rollapply(zoo(cbind(a = 1:6, b = 11:16)), 3, colSums, by.column = FALSE) # these two are the same rollapply(zoo(1:6), 2, sum, by = 2, align = "right") aggregate(zoo(1:6), c(2, 2, 4, 4, 6, 6), sum) # these two are the same rollapply(zoo(1:3), list(1), c) lag(zoo(1:3), 1) # these two are the same rollapply(zoo(1:3), list(1), c) lag(zoo(1:3)) # these two are the same rollapply(zoo(1:5), list(c(1, 0, 1)), sum) rollapply(zoo(1:5), 3, sum) # these two are the same rollapply(zoo(1:5), list(0:2), sum) rollapply(zoo(1:5), 3, sum, align = "left") # these two are the same rollapply(zoo(1:5), list((2:0)), sum) rollapply(zoo(1:5), 3, sum, align = "right") # these two are the same rollapply(zoo(1:6), list(NULL, NULL, (2:0)), sum) rollapply(zoo(1:6), 3, sum, by = 3, align = "right") # these two are the same rollapply(zoo(1:5), list(c(1, 1)), sum) rollapply(zoo(1:5), 3, function(x) sum(x[2])) # these two are the same rollapply(1:5, 3, rev) embed(1:5, 3) # these four are the same x < 1:6 rollapply(c(0, 0, x), 3, sum, align = "right")  x rollapply(x, 3, sum, partial = TRUE, align = "right")  x rollapply(x, 3, function(x) sum(x[3]), partial = TRUE, align = "right") rollapply(x, list((2:1)), sum, partial = 0) # same as Matlab's buffer(x, n, p) for valid nonnegative p # See http://www.mathworks.com/help/toolbox/signal/buffer.html x < 1:30; n < 7; p < 3 t(rollapply(c(rep(0, p), x, rep(0, np)), n, by = np, c)) # these three are the same y < 10 * seq(8); k < 4; d < 2 # 1 # from http://ucfagls.wordpress.com/2011/06/14/embeddingatimeserieswithtimedelayinrpartii/ Embed < function(x, m, d = 1, indices = FALSE, as.embed = TRUE) { n < length(x)  (m1)*d X < seq_along(x) if(n <= 0) stop("Insufficient observations for the requested embedding") out < matrix(rep(X[seq_len(n)], m), ncol = m) out[,1] < out[,1, drop = FALSE] + rep(seq_len(m  1) * d, each = nrow(out)) if(as.embed) out < out[, rev(seq_len(ncol(out)))] if(!indices) out < matrix(x[out], ncol = m) out } Embed(y, k, d) # 2 rollapply(y, list(d * seq(0, k1)), c) # 3 rollapply(y, d*k1, function(x) x[d * seq(k1, 0) + 1])