plot: Plots Permutation Distribution for Nonparametric Tests

Description

plot methods for object classes "np.cor.test", "np.loc.test", and "np.reg.test"

Usage

# S3 method for np.cor.test
plot(x, alpha = 0.05, col = "grey", col.rr = "red",
     col.stat = "black", lty.stat = 2, lwd.stat = 2, 
     xlab = "Test Statistic", main = "Permutation Distribution", 
     breaks = "scott", border = NA, box = TRUE, ...)
           
# S3 method for np.loc.test
plot(x, alpha = 0.05, col = "grey", col.rr = "red",
     col.stat = "black", lty.stat = 2, lwd.stat = 2, 
     xlab = "Test Statistic", main = "Permutation Distribution", 
     breaks = "scott", border = NA, box = TRUE, ...)
           
# S3 method for np.reg.test
plot(x, alpha = 0.05, col = "grey", col.rr = "red",
     col.stat = "black", lty.stat = 2, lwd.stat = 2, 
     xlab = "Test Statistic", main = "Permutation Distribution", 
     breaks = "scott", border = NA, box = TRUE, SQRT = TRUE, ...)

Arguments

x: an object of class "np.cor.test" output by the np.cor.test function, "np.loc.test" output by the np.loc.test function, or "np.reg.test" output by the np.reg.test function
alpha: significance level of the nonparametric test
col: color for plotting the non-rejection region
col.rr: color for plotting the rejection region
col.stat: color for plotting the observed test statistic
lty.stat: line type for plotting the observed test statistic
lwd.stat: line width for plotting the observed test statistic
xlab: x-axis label for the plot
main: title for the plot
breaks: defines the breaks of the histogram (see hist)
border: color of the border around the bars
box: should a box be drawn around the plot?
SQRT: for regression tests, should the permutation distribution (and test statistic) be plotted on the square-root scale?
...: additional arguments to be passed to hist

Author

Nathaniel E. Helwig <helwig@umn.edu>

Details

Plots a histogram of the permutation distribution and the observed test statistic. The argument 'alpha' controls the rejection region of the nonparametric test, which is plotted using a separate color (default is red).

References

Helwig, N. E. (2019). Statistical nonparametric mapping: Multivariate permutation tests for location, correlation, and regression problems in neuroimaging. WIREs Computational Statistics, 11(2), e1457. doi: 10.1002/wics.1457

Examples

Run this code


######******######   np.cor.test   ######******######

# generate data
rho <- 0.5
val <- c(sqrt(1 + rho), sqrt(1 - rho))
corsqrt <- matrix(c(val[1], -val[2], val), 2, 2) / sqrt(2)
set.seed(1)
n <- 50
z <- cbind(rnorm(n), rnorm(n)) %*% corsqrt
x <- z[,1]
y <- z[,2]

# test H0: rho = 0
set.seed(0)
test <- np.cor.test(x, y)

# plot results
plot(test)


######******######   np.loc.test   ######******######

# generate data
set.seed(1)
n <- 50
x <- rnorm(n, mean = 0.5)

# one sample t-test
set.seed(0)
test <- np.loc.test(x)

# plot results
plot(test)


######******######   np.reg.test   ######******######

# generate data
set.seed(1)
n <- 50
x <- cbind(rnorm(n), rnorm(n))
beta <- c(0.25, 0.5)
y <- x %*% beta + rnorm(n)

# Wald test (method = "perm")
set.seed(0)
test <- np.reg.test(x, y)

# plot results
plot(test)

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