WorksheetFunction.BetaInv(Double, Double, Double, Object, Object) Method
Definition
Important
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Returns the inverse of the cumulative distribution function for a specified beta distribution. That is, if probability = BetaDist(x,...), then BetaInv(probability,...) = x.
public double BetaInv (double Arg1, double Arg2, double Arg3, object Arg4, object Arg5);Public Function BetaInv (Arg1 As Double, Arg2 As Double, Arg3 As Double, Optional Arg4 As Object, Optional Arg5 As Object) As DoubleParameters
- Arg1
- Double
A probability associated with the beta distribution.
- Arg2
- Double
The Alpha parameter of the distribution.
- Arg3
- Double
The Beta parameter the distribution.
- Arg4
- Object
An optional lower bound to the interval of x.
- Arg5
- Object
An optional upper bound to the interval of x.
Returns
Remarks
Important: This function has been replaced with one or more new functions that may provide improved accuracy and whose names better reflect their usage. This function is still available for compatibility with earlier versions of Excel. However, if backward compatibility is not required, you should consider using the new functions from now on, because they more accurately describe their functionality. For more information about the new function, see the Beta_Inv(Double, Double, Double, Object, Object) method.
The beta distribution can be used in project planning to model probable completion times given an expected completion time and variability.
- If any argument is nonnumeric, BetaInv generates an error value.
- If alpha ≤ 0 or beta ≤ 0, BetaInv generates an error value.
- If probability ≤ 0 or probability > 1, BetaInv generates an error value.
- If you omit values for A and B, BetaInv uses the standard cumulative beta distribution, so that A = 0 and B = 1.
Given a value for probability, BetaInv seeks that value x such that BetaDist(x, alpha, beta, A, B) = probability. Thus, precision of BetaInv depends on precision of BetaDist(Double, Double, Double, Object, Object). BetaInv uses an iterative search technique. If the search has not converged after 100 iterations, the function generates an error value.