seasonTrend {wql} | R Documentation |
Determine seasonal trends
Description
Finds the trend for each season and each variable in a time series.
Usage
seasonTrend(x, plot = FALSE, type = c("slope", "relative"), pval = 0.05, ...)
Arguments
x |
Time series vector, or time series matrix with column names |
plot |
Should the results be plotted? |
type |
Type of trend to be plotted, actual or relative to series median |
pval |
p-value for significance |
... |
Further options to pass to plotting function |
Details
The Mann-Kendall test is applied for each season and series (in the case of
a matrix). The actual and relative Sen slope (actual divided by median for
that specific season and series); the p-value for the trend; and the
fraction of missing slopes involving the first and last fifths of the data
are calculated (see mannKen
).
If plot = TRUE
, each season for each series is represented by a bar
showing the trend. The fill colour indicates whether or not.
If the fraction of missing slopes is 0.5 or more, the corresponding trends
are omitted.
Parameters can be passed to the plotting function, in particular, to
facet_wrap
in ggplot2. The most useful parameters here are
ncol
(or nrow
), which determines the number of columns (or
rows) of plots, and scales
, which can be set to "free_y"
to
allow the y-axis to change for each time series. Like all ggplot2
objects, the plot output can also be customized extensively by modifying and
adding layers.
Value
A data frame with the following fields:
series |
series names |
season |
season number |
sen.slope |
Sen slope in original units per year |
sen.slope.rel |
Sen slope divided by median for that specific season and series |
p |
p-value for the trend according to the Mann-Kendall test. |
missing |
Proportion of slopes joining first and last fifths of the data that are missing |
Author(s)
Alan Jassby, James Cloern
See Also
mannKen
, plotSeason
,
facet_wrap
Examples
x <- sfbayChla
seasonTrend(x)
seasonTrend(x, plot = TRUE, ncol = 4)