years | R Documentation |
A variety of small utilities used in other functions.
d |
A numeric matrix or data frame with depth in the first column and observations for some variable in each of the remaining columns. |
na.rm |
Should missing data be removed? |
seas |
An integer vector of seasons to be retained. |
sub |
An integer vector. |
w |
A vector of class |
x |
A numeric vector. |
x1 |
A matrix or vector time series. |
y |
A vector of class |
date2decyear
: Converts object of class "Date"
to decimal year
assuming time of day is noon.
decyear2date
: Converts decimal year to object of class "Date"
.
layerMean
: Acts on a matrix or data frame with depth in the first
column and observations for different variables (or different sites, or
different times) in each of the remaining columns. The trapezoidal mean over
the given depths is calculated for each of the variables. Replicate depths
are averaged, and missing values or data with only one unique depth are
handled. Data are not extrapolated to cover missing values at the top or
bottom of the layer. The result can differ markedly from the simple mean
even for equal spacing of depths, because the top and bottom values are
weighted by 0.5 in a trapezoidal mean.
leapYear
: TRUE
if x
is a leap year, FALSE
otherwise.
meanSub
: Mean of a subset of a vector.
monthNum
: Converts dates to the corresponding numeric month.
tsSub
: Drops seasons from a matrix or vector time series.
years
: Converts dates to the corresponding numeric years.
dates <- as.Date(c("1996-01-01", "1999-12-31", "2004-02-29", "2005-03-01"))
date2decyear(dates)
decyear2date(c(1996.0014, 1999.9986, 2004.1626, 2005.1630))
z <- c(1, 2, 3, 5, 10) # 5 depths
x <- matrix(rnorm(30), nrow = 5) # 6 variables at 5 depths
layerMean(cbind(z, x))
leapYear(seq(1500, 2000, 100))
leapYear(c(1996.9, 1997))
## Aggregate monthly time series over Feb-Apr only.
aggregate(sfbayChla, 1, meanSub, sub = 2:4)
monthNum(as.Date(c("2007-03-17", "2003-06-01")))
## Ignore certain seasons in a Seasonal Kendall test.
c27 <- sfbayChla[, "s27"]
seaKen(tsSub(c27)) # Aug and Dec missing the most key data
seaKen(tsSub(c27, seas = c(1:7, 9:11)))
y <- Sys.time()
years(y)
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