function [ n_data, sam, suc, pop, n, fx ] = hypergeometric_cdf_values ( n_data ) %*****************************************************************************80 % %% HYPERGEOMETRIC_CDF_VALUES returns some values of the hypergeometric CDF. % % Discussion: % % CDF(X)(A,B) is the probability of at most X successes in A trials, % given that the probability of success on a single trial is B. % % In Mathematica, the function can be evaluated by: % % Needs["Statistics`DiscreteDistributions`] % dist = HypergeometricDistribution [ sam, suc, pop ] % CDF [ dist, n ] % % Licensing: % % This code is distributed under the GNU LGPL license. % % Modified: % % 16 September 2004 % % Author: % % John Burkardt % % Reference: % % Milton Abramowitz and Irene Stegun, % Handbook of Mathematical Functions, % US Department of Commerce, 1964. % % Stephen Wolfram, % The Mathematica Book, % Fourth Edition, % Wolfram Media / Cambridge University Press, 1999. % % Daniel Zwillinger, % CRC Standard Mathematical Tables and Formulae, % 30th Edition, CRC Press, 1996, pages 651-652. % % Parameters: % % Input/output, integer N_DATA. The user sets N_DATA to 0 before the % first call. On each call, the routine increments N_DATA by 1, and % returns the corresponding data; when there is no more data, the % output value of N_DATA will be 0 again. % % Output, integer SAM, integer SUC, integer POP, the sample size, % success size, and population parameters of the function. % % Output, integer N, the argument of the function. % % Output, real FX, the value of the function. % n_max = 16; fx_vec = [ ... 0.6001858177500578E-01, ... 0.2615284665839845E+00, ... 0.6695237889132748E+00, ... 0.1000000000000000E+01, ... 0.1000000000000000E+01, ... 0.5332595856827856E+00, ... 0.1819495964117640E+00, ... 0.4448047017527730E-01, ... 0.9999991751316731E+00, ... 0.9926860896560750E+00, ... 0.8410799901444538E+00, ... 0.3459800113391901E+00, ... 0.0000000000000000E+00, ... 0.2088888139634505E-02, ... 0.3876752992448843E+00, ... 0.9135215248834896E+00 ]; n_vec = [ ... 7, 8, 9, 10, ... 6, 6, 6, 6, ... 6, 6, 6, 6, ... 0, 0, 0, 0 ]; pop_vec = [ ... 100, 100, 100, 100, ... 100, 100, 100, 100, ... 100, 100, 100, 100, ... 90, 200, 1000, 10000 ]; sam_vec = [ ... 10, 10, 10, 10, ... 6, 7, 8, 9, ... 10, 10, 10, 10, ... 10, 10, 10, 10 ]; suc_vec = [ ... 90, 90, 90, 90, ... 90, 90, 90, 90, ... 10, 30, 50, 70, ... 90, 90, 90, 90 ]; if ( n_data < 0 ) n_data = 0; end n_data = n_data + 1; if ( n_max < n_data ) n_data = 0; sam = 0; suc = 0; pop = 0; n = 0; fx = 0.0; else sam = sam_vec(n_data); suc = suc_vec(n_data); pop = pop_vec(n_data); n = n_vec(n_data); fx = fx_vec(n_data); end return end