| sk_seasonal | R Documentation | 
Non-parametric test for monotonic seasonal trends
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),
  ...
)
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.  | 
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.
Returns a data.frame object or a summary from EnvStats::kendallSeasonalTrendTest
Julie Padilla
assign_season, y_labeler, kendallSeasonalTrendTest
dat_wq <- elksmwq
dat_wq <- qaqc(dat_wq, qaqc_keep = c(0, 3, 5))
x <- sk_seasonal(dat_wq, param = 'temp')
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