sk_seasonal {SWMPrExtension} | R Documentation |
Seasonal Kendall Analysis for Seasonal Data
Description
Non-parametric test for monotonic seasonal trends
Usage
sk_seasonal(swmpr_in, ...)
## S3 method for class 'swmpr'
sk_seasonal(
swmpr_in,
param = NULL,
alpha = 0.05,
data_min = 5,
envStats_summary = FALSE,
stat_lab = "Average",
FUN = function(x) mean(x, na.rm = TRUE),
...
)
Arguments
swmpr_in |
input swmpr object |
... |
additional arguments passed to other methods. See |
param |
chr string of variable to plot |
alpha |
num, alpha value to use to significance test. Defaults to 0.05. |
data_min |
num, the minimum number of observations required to perform the analysis. Defaults to 5 |
envStats_summary |
logical, should the standard |
stat_lab |
chr, label for the summary statistic defined in |
FUN |
function used to aggregate seasonal SWMP data. |
Details
This function performs a seasonal kendall test on seasonally aggregated values using kendallSeasonalTrendTest
.
Data are aggregated on a user-specified seasonal basis using the FUN
argument. For example, using default settings, sk_seasonal
would perform a seasonal kendall test on average monthly values. However, if the user set FUN = min(x, na.rm = TRUE)
then a seasonal kendall would be performed on monthly minimum values.
If EnvStats_summary = TRUE
then the detailed output summary from kendallSeasonalTrendTest
will be returned. If EnvStats_summary = FALSE
then an abbreviated summary will be returned in a data.frame
. The abbreviated summary contains the station name, the type of statistic used to summarize the data on a seasonal basis (specified by stat_lab
), and the following results from kendallSeasonalTrendTest
: tau, slope, p-value for the chi-square test, and the p-value for the trend test.
Value
Returns a data.frame
object or a summary from EnvStats::kendallSeasonalTrendTest
Author(s)
Julie Padilla
See Also
assign_season
, y_labeler
, kendallSeasonalTrendTest
Examples
dat_wq <- elksmwq
dat_wq <- qaqc(dat_wq, qaqc_keep = c(0, 3, 5))
x <- sk_seasonal(dat_wq, param = 'temp')