cdfGam#
Purpose#
Computes the regularized lower incomplete gamma function.
Format#
- p = cdfGam(x, intlim)#
- Parameters:
x (NxK matrix) – Values at which to evaluate the regularized lower incomplete gamma function. \(x > 0\).
int_lim (LxM matrix) – ExE compatible with x, containing the integration limit. \(int\_lim > 0\).
- Returns:
p (matrix, max(N,L) by max(K,M)) – Each element in p is the regularized lower incomplete gamma function evaluated at the corresponding element in x.
Examples#
Basic example#
p = cdfGam(1.2, 3);
After the above code, P will equal
0.9287
Matrix example#
// Create a 1x4 row vector
x = { 0.5 1 3 10 };
// Create a 6x1 column vector: 0, 0.2, 0.4, ..., 1.0
int_lim = seqa(0,.2,6);
/*
** Compute for all combinations of the elements
** of 'x' and 'int_lim'
*/
p = cdfGam(x, int_lim);
print "intlim = " int_lim;
print "p = " p;
After the code above:
intlim =
0.00000000
0.20000000
0.40000000
0.60000000
0.80000000
1.0000000
p =
0.00000000 0.00000000 0.00000000 0.00000000
0.47291074 0.18126925 0.0011484812 2.3530688e-014
0.62890663 0.32967995 0.0079263319 2.0098099e-011
0.72667832 0.45118836 0.023115288 9.6697183e-010
0.79409679 0.55067104 0.047422596 1.4331002e-008
0.84270079 0.63212056 0.080301397 1.1142548e-007
This computes the integrals over the range from 0 to 1, in increments of 0.2, at the parameter values 0.5, 1, 3, 10.
Remarks#
The regularized lower incomplete gamma function returns the integral
\[\text{cdfGam(x, int_lim)} = \int_{0}^{int\_lim} \frac{e^{-t}t^{(x-1)}}{\Gamma(x)}dt\]
A -1 is returned for those elements with invalid inputs.