miscor (version 0.1-0)

plot.sim.seqtest.cor: Plot sim.seqtest

Description

This function plots the sim.seqtest.cor object

Usage

"plot"(x, plot.lines = TRUE, plot.nom = TRUE, ylim = NULL, type = "b", pch = 19, lty = 1, lwd = 1, ...)

Arguments

x

sim.seqtest.cor object.

plot.lines

plot lines connecting points withe the x- and y-axis.

plot.nom

plot line at the nominal alpha.

ylim

the y limits of the plot.

type

what type of plot should be drawn ("p" for points, "l" for lines and "b" for both).

pch

plotting character.

lty

line type.

lwd

line width.

...

further arguments passed to or from other methods.

References

Schneider, B., Rasch, D., Kubinger, K. D., & Yanagida, T. (2015). A Sequential triangular test of a correlation coefficient's null-hypothesis: 0 $< \rho \le \rho$0. Statistical Papers, 56, 689-699.

See Also

sim.seqtest.cor, seqtest.cor

Examples

## Not run: 
# 
# #---------------------------------------------
# # Determine optimal k and nominal type-II-risk
# # H0: rho <= 0.3, H1: rho > 0.3
# # alpha = 0.01, beta = 0.05, delta = 0.25
# 
# # Step 1: Determine the optimal size of subsamples (k)
# 
# sim.obj.1 <- sim.seqtest.cor(rho.sim = 0.3, k = seq(4, 16, by = 1), rho = 0.3,
#                              alternative = "greater",
#                              delta = 0.25, alpha = 0.05, beta = 0.05,
#                              runs = 10000)
# 
# plot(sim.obj.1)
# 
# # Step 2: Determine the optimal nominal type-II-risk based on
# #         the optimal size of subsamples (k) from step 1
# 
# sim.obj.2 <- sim.seqtest.cor(rho.sim = 0.55, k = 16, rho = 0.3,
#                              alternative = "greater",
#                              delta = 0.25, alpha = 0.05, beta = seq(0.05, 0.15, by = 0.01),
#                              runs = 10000)
# 
# plot(sim.obj.2)
# ## End(Not run)