Replace NA by Interpolation
Generic functions for replacing each NA with interpolated
values.
na.approx(object, ...) ## S3 method for class 'zoo' na.approx(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along) ## S3 method for class 'zooreg' na.approx(object, ...) ## S3 method for class 'ts' na.approx(object, ...) ## Default S3 method: na.approx(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along) na.spline(object, ...) ## S3 method for class 'zoo' na.spline(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along) ## S3 method for class 'zooreg' na.spline(object, ...) ## S3 method for class 'ts' na.spline(object, ...) ## Default S3 method: na.spline(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along)
object |
object in which |
x, xout |
Variables to be used for interpolation as in |
na.rm |
logical. If the result of the (spline) interpolation
still results in leading and/or trailing |
maxgap |
maximum number of consecutive |
along |
deprecated. |
... |
further arguments passed to methods. The |
It can also be used for series disaggregation by specifying xout.
By default the index associated with object is used
for interpolation. Note, that if this calls index.default
this gives an equidistant spacing 1:NROW(object). If object
is a matrix or data.frame, the interpolation is done separately for
each column.
If obj is a plain vector then na.approx(obj, x, y, xout, ...)
returns approx(x = x[!na], y = coredata(obj)[!na], xout = xout, ...)
(where na indicates observations with NA) such that xout
defaults to x. Note that if there are less than two non-NAs then
approx() cannot be applied and thus no NAs can be replaced.
If obj is a zoo, zooreg or ts object its
coredata value is processed as described and its time index is xout if
specified and index(obj) otherwise. If obj is two dimensional
then the above is applied to each column separately. For examples, see below.
If obj has more than one column, the above strategy is applied to
each column.
An object of similar structure as object with NAs replaced by
interpolation. For na.approx only the internal NAs are replaced and
leading or trailing NAs are omitted if na.rm = TRUE or not
replaced if na.rm = FALSE.
z <- zoo(c(2, NA, 1, 4, 5, 2), c(1, 3, 4, 6, 7, 8))
## use underlying time scale for interpolation
na.approx(z)
## use equidistant spacing
na.approx(z, 1:6)
# with and without na.rm = FALSE
zz <- c(NA, 9, 3, NA, 3, 2)
na.approx(zz, na.rm = FALSE)
na.approx(zz)
d0 <- as.Date("2000-01-01")
z <- zoo(c(11, NA, 13, NA, 15, NA), d0 + 1:6)
# NA fill, drop or keep leading/trailing NAs
na.approx(z)
na.approx(z, na.rm = FALSE)
# extrapolate to point outside of range of time points
# (a) drop NA, (b) keep NA, (c) extrapolate using rule = 2 from approx()
na.approx(z, xout = d0 + 7)
na.approx(z, xout = d0 + 7, na.rm = FALSE)
na.approx(z, xout = d0 + 7, rule = 2)
# use splines - extrapolation handled differently
z <- zoo(c(11, NA, 13, NA, 15, NA), d0 + 1:6)
na.spline(z)
na.spline(z, na.rm = FALSE)
na.spline(z, xout = d0 + 1:6)
na.spline(z, xout = d0 + 2:5)
na.spline(z, xout = d0 + 7)
na.spline(z, xout = d0 + 7, na.rm = FALSE)
## using na.approx for disaggregation
zy <- zoo(1:3, 2000:2001)
# yearly to monthly series
zmo <- na.approx(zy, xout = as.yearmon(2000+0:13/12))
zmo
# monthly to daily series
sq <- seq(as.Date(start(zmo)), as.Date(end(zmo), frac = 1), by = "day")
zd <- na.approx(zmo, x = as.Date, xout = sq)
head(zd)
# weekly to daily series
zww <- zoo(1:3, as.Date("2001-01-01") + seq(0, length = 3, by = 7))
zww
zdd <- na.approx(zww, xout = seq(start(zww), end(zww), by = "day"))
zdd
# The lines do not show up because of the NAs
plot(cbind(z, z), type = "b", screen = 1)
# use na.approx to force lines to appear
plot(cbind(z, na.approx(z)), type = "b", screen = 1)
# Workaround where less than 2 NAs can appear in a column
za <- zoo(cbind(1:5, NA, c(1:3, NA, 5), NA)); za
ix <- colSums(!is.na(za)) > 0
za[, ix] <- na.approx(za[, ix]); za
# using na.approx to create regularly spaced series
# z has points at 10, 20 and 40 minutes while output also has a point at 30
if(require("chron")) {
tt <- as.chron("2000-01-01 10:00:00") + c(1, 2, 4) * as.numeric(times("00:10:00"))
z <- zoo(1:3, tt)
tseq <- seq(start(z), end(z), by = times("00:10:00"))
na.approx(z, xout = tseq)
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