#Wald WOlf 2s Test:
sqlstr <- paste0("SELECT * FROM tblWW2SMulti WHERE DATASETID = 1")
res <- sqlQuery(connection, sqlstr)
Renv = new.env(parent = globalenv())
Renv$x <- res$num_val[res$groupid == 1]
Renv$y <- res$num_val[res$groupid == 2]
FLenv = as.FL(Renv)
Renv$res1 <- runs.test(Renv$x, Renv$y, alternative = "two.sided")
FLenv$res1 <- WaldWolftest2s(FLenv$x, FLenv$y)
test_that("Wald-Wolfowitz two Sample Test:",{
result = eval_expect_equal({
p.val <- res1$p.value
z <- res1$statistic
},Renv,FLenv,
noexpectation=c("res1"),
expectation =c( "p.val", "z"),
verbose=T,
check.attributes=FALSE)
})
#Wald-Wolf Test 2s
Renv = new.env(parent = globalenv())
Renv$a = c(35,44,39,50,48,29,60,75,49,66)
Renv$b = c(17, 23, 13, 24, 33, 21, 18, 16, 32)
FLenv = as.FL(Renv)
FLenv$res1 <- WaldWolftest2s(FLenv$a, FLenv$b)
Renv$res1 <- runs.test(Renv$a, Renv$b, alternative = "two.sided")
# source: http://www.statext.com/practice/WaldWolfowitzRunsTestTwo02.php
#result of source gives Z = -2.83 which is same as computed by FL Test
test_that("Wald-Wolfowitz two Sample Test:",{
result = eval_expect_equal({
p.val <- res1$p.value
z <- res1$statistic
},Renv,FLenv,
noexpectation=c("res1"),
expectation =c( "p.val", "z"),
verbose=T,
check.attributes=FALSE)
})
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