Performs a one- or two-sample Kolmogorov-Smirnov test. Includes the option to perform the two-sample test using the formula notation.
ksTest(x, ...) # S3 method for default ksTest(x, y, ..., alternative = c("two.sided", "less", "greater"), exact = NULL) # S3 method for formula ksTest(x, data = NULL, ..., alternative = c("two.sided", "less", "greater"), exact = NULL)
x | A numeric vector of data values or a formula (see details). |
---|---|
… | Parameters of the distribution specified (as a character string) by |
y | A numeric vector of data values, a character string naming a cumulative distribution function, or an actual cumulative distribution function. See |
alternative | A string that indicates the alternative hypothesis. See |
exact |
|
data | A data frame that contains the variables in the formula for |
See ks.test
.
This is exactly ks.test
except that a formula may be used for the two-sample situation. The default version is simply a pass through to ks.test
. See ks.test
for more details.
## see ks.test for other examples x <- rnorm(50) y <- runif(30) df <- data.frame(dat=c(x,y),grp=rep(c("X","Y"),c(50,30))) ## one-sample (from ks.test) still works ksTest(x+2, "pgamma", 3, 2)#> #> One-sample Kolmogorov-Smirnov test #> #> data: x #> D = 0.21652, p-value = 0.01546 #> alternative hypothesis: two-sided #>ks.test(x+2, "pgamma", 3, 2)#> #> One-sample Kolmogorov-Smirnov test #> #> data: x + 2 #> D = 0.21652, p-value = 0.01546 #> alternative hypothesis: two-sided #>## first two-sample example in ?ks.test ksTest(x,y)#> #> Two-sample Kolmogorov-Smirnov test #> #> data: x and y #> D = 0.6, p-value = 8.598e-07 #> alternative hypothesis: two-sided #>ks.test(x,y)#> #> Two-sample Kolmogorov-Smirnov test #> #> data: x and y #> D = 0.6, p-value = 8.598e-07 #> alternative hypothesis: two-sided #>## same as above but using data.frame and formula ksTest(dat~grp,data=df)#> #> Two-sample Kolmogorov-Smirnov test #> #> data: x and y #> D = 0.6, p-value = 8.598e-07 #> alternative hypothesis: two-sided #>