ks.test.imp: Kolmogorov-Smirnov Tests In kolmim: An Improved Evaluation of Kolmogorov's Distribution

Description

Perform a one-sample two-sided exact Kolmogorov-Smirnov test, similarly to `ks.test` from package `stats`, but using an improved routine.

Usage

 `1` ```ks.test.imp(x, y, ...) ```

Arguments

 `x` a numeric vector of data values. `y` either a numeric vector of data values, or a character string naming a cumulative distribution function or an actual cumulative distribution function such as `pnorm`. Only continuous CDFs are valid. `...` parameters of the distribution specified (as a character string) by `y`.

Details

This routine is equivalent to `ks.test(x, y, ..., exact=TRUE)` but uses an improved method based on `pkolmim`. For more details about the arguments, please refer to the documentation for `ks.test`.

Value

A list with class `"htest"` containing the following components:

 `statistic` the value of the test statistic. `p.value` the p-value of the test. `alternative` "two-sided". `method` a character string indicating what type of test was performed. `data.name` a character string giving the name(s) of the data.

Source

The two-sided one-sample distribution comes via Carvalho (2015).

References

Luis Carvalho (2015), An Improved Evaluation of Kolmogorov's Distribution. Journal of Statistical Software, 65/3, 1–7. http://www.jstatsoft.org/v65/c03/.

`pkolmim` for the cumulative distribution function of Kolmogorov's goodness-of-fit measure.

Examples

 ```1 2 3 4 5 6 7 8 9``` ```x <- abs(rnorm(100)) p.kt <- ks.test(x, "pexp", exact = TRUE)\$p p.ktimp <- ks.test.imp(x, "pexp")\$p abs(p.kt - p.ktimp) # compare execution times x <- abs(rnorm(2000)) system.time(ks.test.imp(x, "pexp")) system.time(ks.test(x, "pexp", exact = TRUE)) ```

Example output

```[1] 5.551115e-16
user  system elapsed
0.393   0.000   0.394
user  system elapsed
1.475   0.001   1.475
```

kolmim documentation built on May 30, 2017, 5:32 a.m.