conover {ANSM5} | R Documentation |
Perform Conover test using standard or squared ranks
Description
conover()
performs the Conover test using standard or squared ranks and is used in chapters 6 and 7 of "Applied Nonparametric Statistical Methods" (5th edition)
Usage
conover(
x,
y,
H0 = NULL,
alternative = c("two.sided", "less", "greater"),
abs.ranks = FALSE,
max.exact.perms = 5e+06,
nsims.mc = 10000,
seed = NULL,
do.asymp = FALSE,
do.exact = TRUE,
do.mc = FALSE
)
Arguments
x |
Numeric vector of same length as y |
y |
Factor of same length as x |
H0 |
Null hypothesis value (defaults to |
alternative |
Type of alternative hypothesis (defaults to |
abs.ranks |
Boolean indicating whether absolute ranks to be used instead of squared ranks (defaults to |
max.exact.perms |
Maximum number of permutations allowed for exact calculations (defaults to |
nsims.mc |
Number of Monte Carlo simulations to be performed (defaults to |
seed |
Random number seed to be used for Monte Carlo simulations (defaults to |
do.asymp |
Boolean indicating whether or not to perform asymptotic calculations (defaults to |
do.exact |
Boolean indicating whether or not to perform exact calculations (defaults to |
do.mc |
Boolean indicating whether or not to perform Monte Carlo calculations (defaults to |
Value
An ANSMtest object with the results from applying the function
Examples
# Example 6.13 from "Applied Nonparametric Statistical Methods" (5th edition)
conover(ch6$typeA, ch6$typeB, do.exact = FALSE, do.asymp = TRUE)
# Exercise 7.15 from "Applied Nonparametric Statistical Methods" (5th edition)
conover(ch7$braking.distance.2, ch7$initial.speed, do.exact = FALSE, do.asymp = TRUE)