Renv = new.env(parent = globalenv())
Renv$df1 = cbind(x = 1:10, y = c(1:3, 8:5, 8:10))
Renv$wt1 = c(0,0,0,1,1,1,1,1,0,0)
FLenv <- as.FL(Renv)
#Test failed . Diffrent covariance result matrix and different weight list too.
#Asana Ticket - https://app.asana.com/0/143316600934101/145657030318423
test_that("Check for weighted covariance with unbiased method",{
result = eval_expect_equal({
test1 = cov.wt(df1, wt = wt1)
}, Renv,FLenv)
})
#test Failed. Different results for R and AdapteR.
#Asana Ticket - https://app.asana.com/0/143316600934101/145657030318423
test_that("Check for weighted covariance with ML method",{
result = eval_expect_equal({
test2 = cov.wt(df1, wt = wt1,method = "ML",cor = TRUE)
}, Renv,FLenv)
})
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