mcovarTopN
Syntax
mcovarTopN(X, Y, S, window, top, [ascending=true],
[tiesMethod='oldest'])
Please see mTopN for the parameters and windowing logic.
Details
Within a sliding window of given length (measured by the number of elements), the function stably sorts X and Y by S in the order specified by ascending, then calculates the moving covariance of the first top pairs of elements in X and Y.
Examples
x = NULL 3 8 4 0
y = 2 3 1 7 3
s = 5 NULL 8 9 4
mcovarTopN(x, y, s, 3, 2)
// output
[ , , , -12, -8]
s2=2021.01.01 2021.02.03 2021.01.23 2021.04.06 2021.12.29
mcovarTopN(x, y, s2, 3, 2)
// output
[ , , , -5, -12]
x1 = matrix(x, 4 3 6 2 3)
y1=matrix(3 7 9 3 2, y)
s1=matrix(2 3 1 7 3, s)
mcovarTopN(x, y1, s1, 3, 2)| col1 | col2 |
|---|---|
| 5 | -5 |
| 28 | -8 |
mcovarTopN(x1, y1, s, 3, 2)| col1 | col2 |
|---|---|
| -0.5 | |
| -0.5 | |
| 5 | -3 |
| 28 | -3 |
mcovarTopN(x1, y1, s1, 3, 2)| col1 | col2 |
|---|---|
| -0.5 | |
| -0.5 | |
| 5 | -3 |
| 28 | -3 |
n = 3000
ids = 1..3000
dates = take(2021.01.01..2021.10.01,n)
prices = rand(1000,n)
vals = rand(1000,n)
t = table(ids as id,dates as date,prices as price,vals as val)
dbName = "dfs://test_mcovarTopN_2"
if(existsDatabase(dbName))dropDB(dbName)
db = database(dbName,VALUE,1..5000)
pt = db.createPartitionedTable(t,"pt",`id).append!(t)
select mcovarTopN(price, val, id, 10, 5, true) from pt where date>2021.05.01Related function: mcovar