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mincalct.m Modification of mincalc . Assumes mincalc has been run, calls for new target vectors and performs same calculations as mincalc.
% MINCALCT file mincalct.m Aditional target probabilities
% Version of 9/1/93 Updated for version 5 on 6/6/97
% Assumes a data file which includes% 1. Call for minvecq to set q basic minterm vectors.
% 2. Data vectors DV. The first combination is always A|Ac.% 3. Row matrix DP of data probabilities. The first entry is always 1.
TV = input('Enter matrix of target Boolean combinations ');[md,nd] = size(DV);[mt,nt] = size(TV);MT = 1:mt;
rd = rank(DV);CT = zeros(1,mt); % Identification of computable target probabilities
for j = 1:mtCT(j) = rd == rank([DV;TV(j,:)]);end
ct = find(CT);CCT = TV(ct,:)/DV; % Determination of coefficients for computable targets
ctp = DP*CCT'; % Determination of probabilitiesdisp(' Computable target probabilities')
disp([MT(ct); ctp]')
minprob.m
function y = minprob(p)
calculates minterm probabilities
for the basic probabilities in row or column vector
p . Uses the m-functions
mintable, colcopy .
function y = minprob(p)
% MINPROB y = minprob(p) Minterm probs for independent events% Version of 4/7/96
% p is a vector [P(A1) P(A2) ... P(An)], with
% {A1,A2, ... An} independent.% y is the row vector of minterm probabilities
% Uses the m-functions mintable, colcopyn = length(p);
M = mintable(n);a = colcopy(p,2^n); % 2^n columns, each the vector p
m = a.*M + (1 - a).*(1 - M); % Puts probabilities into the minterm% pattern on its side (n by 2^n)
y = prod(m); % Product of each column of m
imintest.m
function y = imintest(pm)
checks minterm probabilities
for independence.
function y = imintest(pm)
% IMINTEST y = imintest(pm) Checks minterm probs for independence% Version of 1/25//96
% Checks minterm probabilities for independence% Uses the m-functions mintable and minprob
m = length(pm);n = round(log(m)/log(2));
if m ~= 2^ny = 'The number of minterm probabilities is incorrect';
elseP = mintable(n)*pm';
pt = minprob(P');a = fix(n/2);
s = abs(pm - pt)>1e-7;
if sum(s)>0
disp('The class is NOT independent')disp('Minterms for which the product rule fails')
y = reshape(s,2^a,2^(n-a));else
y = 'The class is independent';end
end
ikn.m
function y = ikn(P,k)
determines the probability of the
occurrence of exactly
k of the
n independent events whose probabilities are in row or
column vector
P
(
k may be a row or column vector of nonnegative integers
less than or equal to
n ).
function y = ikn(P,k)
% IKN y = ikn(P,k) Individual probabilities of k of n successes% Version of 5/15/95
% Uses the m-functions mintable, minprob, csortn = length(P);
T = sum(mintable(n)); % The number of successes in each mintermpm = minprob(P); % The probability of each minterm
[t,p]= csort(T,pm); % Sorts and consolidates success numbers
% and adds corresponding probabilitiesy = p(k+1);
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