kendallSeasonalTrendTest {WRTDStidal}

Kendall seasonal trend test

Description

Nonparametric test for monotonic trend Within each season based on Kendall's Tau statistic

Usage

kendallSeasonalTrendTest(y, ...)

## Default S3 method:
kendallSeasonalTrendTest(
  y,
  season,
  year,
  alternative = "two.sided",
  correct = TRUE,
  ci.slope = TRUE,
  conf.level = 0.95,
  independent.obs = TRUE,
  data.name = NULL,
  season.name = NULL,
  year.name = NULL,
  parent.of.data = NULL,
  subset.expression = NULL,
  ...
)

## S3 method for class 'data.frame'
kendallSeasonalTrendTest(y, ...)

## S3 method for class 'formula'
kendallSeasonalTrendTest(y, data = NULL, subset, na.action = na.pass, ...)

## S3 method for class 'matrix'
kendallSeasonalTrendTest(y, ...)

Arguments

y

an object containing data for the trend test. In the default method, the argument y must be numeric vector of observations. When y is a data frame, all columns must be numeric. When y is a matrix, it must be a numeric matrix. In the formula method, y must be a formula of the form y ~ season + year, where y, season, and year specify what variables to use for the these arguments in the call to kendallSeasonalTrendTest.default. Missing (NA), undefined (NaN), and infinite (Inf, -Inf) values are allowed but will be removed.

...

methods passed to or from other methods

season

numeric or character vector or a factor indicating the seasons in which the observations in y were taken. The length of season must equal the length of y.

year

numeric vector indicating the years in which the observations in y were taken. The length of year must equal the length of y.

alternative

character string indicating the kind of alternative hypothesis. The possible values are "two.sided" (tau not equal to 0; the default), "less" (tau less than 0), and "greater" (tau greater than 0).

correct

logical scalar indicating whether to use the correction for continuity in computing the z-statistic that is based on the test statistic S'. The default value is TRUE.

ci.slope

logical scalar indicating whether to compute a confidence interval for the slope. The default value is TRUE.

conf.level

numeric scalar between 0 and 1 indicating the confidence level associated with the confidence interval for the slope. The default value is 0.95.

independent.obs

logical scalar indicating whether to assume the observations in y are seially independent. The default value is TRUE.

data.name

character string indicating the name of the data used for the trend test. The default value is deparse(substitute(y)).

season.name

character string indicating the name of the data used for the season. The default value is deparse(substitute(season)).

year.name

character string indicating the name of the data used for the year. The default value is deparse(substitute(year)).

parent.of.data

character string indicating the source of the data used for the trend test.

subset.expression

character string indicating the expression used to subset the data.

data

specifies an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which kendallTrendTest is called.

subset

specifies an optional vector specifying a subset of observations to be used.

na.action

specifies a function which indicates what should happen when the data contain NAs. The default is na.pass.

Details

Perform a nonparametric test for a monotonic trend within each season based on Kendall's tau statistic, and optionally compute a confidence interval for the slope across all seasons.

Value

A list object with elements for results of the test

References

Hirsch, R.M., Slack, J.R., Smith, R.A. 1982. Techniques of trend analysis for monthly water quality data. Water Resources Research, 18:107-121.

Millard, S. P. 2013. EnvStats: An R Package for Environmental Statistics. Springer, New York.

Examples

kendallSeasonalTrendTest(res ~ month + year, tidfitmean)