I recently came across a problem with a dataset I have, since its "resolution" is way too small. The dataset is charaterized to have a maximum (0) which is not really its maximum, since all the numbers are normalized to the higher number found within its "resolution", which is basically the "1 by 1 unit" of the "X" column. The Y values are always similar to a parabolic curve.
Y X
-34,32 -93
-16,56 -92
-10,04 -91
-6,03 -90
-3,34 -89
-1,56 -88
-0,47 -87
0 -86
-0,10 -85
-0,78 -84
-2,11 -83
-4,20 -82
-7,36 -81
-12,31 -80
-22,03 -79
-25,17 -78
Now, I know for sure that the 0 should be somewhere between 0 and -0,10 or between 0 and -0,47. A linear interpolation would give me too much error, so I guess I would use a Cubic Spline.
What I need to do is to calculate the X parameter where my Y REALLY is = 0.
Too bad I couldn't use what I found on Internet because every function I try calculates Y from a specified X (below an example of code). Can anyone help?
Function SpLine(PeriodCol As Range, RateCol As Range, x As Range)
Dim Period_Count As Integer
Dim Rate_Count As Integer
Dim c As Integer
Dim n As Integer
Dim i, k As Integer
Dim p, qn, sig, un As Single
Dim klo, khi As Integer
Dim h, b, a As Single
' shows the calculation of a cubic spline interpolated value given known values for fixed periods
Period_Count = PeriodCol.Rows.Count
Rate_Count = RateCol.Rows.Count
If Period_Count <> Rate_Count Then
SpLine = "Error: Range count dos not match"
GoTo endnow
End If
ReDim xin(Period_Count) As Single
ReDim yin(Period_Count) As Single
For c = 1 To Period_Count
xin(c) = PeriodCol(c)
yin(c) = RateCol(c)
Next c
ReDim u(Period_Count - 1) As Single
ReDim yt(Period_Count) As Single
n = Period_Count
yt(1) = 0
u(1) = 0
For i = 2 To n - 1
sig = (xin(i) - xin(i - 1)) / (xin(i + 1) - xin(i - 1))
p = sig * yt(i - 1) + 2
yt(i) = (sig - 1) / p
u(i) = (yin(i + 1) - yin(i)) / (xin(i + 1) - xin(i)) - (yin(i) - yin(i - 1)) / (xin(i) - xin(i - 1))
u(i) = (6 * u(i) / (xin(i + 1) - xin(i - 1)) - sig * u(i - 1)) / p
Next i
qn = 0
un = 0
yt(n) = (un - qn * u(n - 1)) / (qn * yt(n - 1) + 1)
For k = n - 1 To 1 Step -1
yt(k) = yt(k) * yt(k + 1) + u(k)
Next k
klo = 1
khi = n
Do
k = khi - klo
If xin(k) > x Then
khi = k
Else
klo = k
End If
k = khi - klo
Loop While k > 1
h = xin(khi) - xin(klo)
a = (xin(khi) - x) / h
b = (x - xin(klo)) / h
SpLine = a * yin(klo) + b * yin(khi) + ((a ^ 3 - a) * yt(klo) + (b ^ 3 - b) * yt(khi)) * (h ^ 2) / 6
endnow:
End Function