How to get a specific p-value instead of a range using a Watson's Two-Sample test

#> Attaching package: 'circular'
#> The following objects are masked from 'package:stats':
#>     sd, var

x_prex_wtt <- data.frame(c(57,88,90,100,25,90,46,77,38,35,29,23,27,13,18,55,33,55 ))
y_prex_wtt <- data.frame(c(2,24,210,180,145,1,88,30,170,177,16,44,315,300,320,189,15,177))
xCircular_wtt <-  circular(x_prex_wtt, units = "degrees", template = "geographics")
yCircular_wtt <-  circular(y_prex_wtt, units = "degrees", template = "geographics")
#>       Watson's Two-Sample Test of Homogeneity 
#> Test Statistic: 0.3839 
#> 0.001 < P-value < 0.01 

Instead of getting a range for where the p-value is, I need a specific p-value.

Any suggestions?


Tey setting an alpha?

I dont know the mathematics of this test, so I can't speak for how well the functions serve their purpose

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Are you suggesting continuously setting an alpha level until you get close enough to what the actual p-value is?

I'm gonna try it, but I am looking for the actual p-value, not what it is greater than or less than or in a range between.

watson.two.test(xCircular_wtt,yCircular_wtt,alpha = 0.002)
#> Error in watson.two.test(xCircular_wtt, yCircular_wtt, alpha = 0.002): could not find function "watson.two.test"

Actually, if I don't pick an alpha level at 0.1,0.05, or 0.001 I get this error message.