Description Usage Arguments Value Examples
Let p=(p1,...,pn)
be a probability distribution
which belongs to a lower dimensional polytope of the n-dimensional
simplex. The polytope is defined by a collection of linear
equality and inequality constraints. A dependent sequence of the
p's are generated by a Markov chain using the Metropolis-Hastings
algorithm whose stationary distribution is the uniform distribution
over the polytope. This is done by generating k blocks
of size step
where the last member of each is returned.
1 | constrppprob(A1,A2,A3,b1,b2,b3,initsol,step,k)
|
A1 |
The matrix for the equality constraints.This must always
contain the constraint |
A2 |
The matrix for the |
A3 |
The matrix for the |
b1 |
The rhs vector for |
b2 |
The rhs vector for |
b3 |
The rhs vector for |
initsol |
A vector which lies in the interior of the polytope. |
step |
The number of |
k |
The total number of blocks generated and hence the number
of |
The returned value is a k by n matrix of probability vectors.
1 2 3 4 5 6 7 8 |
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