From 8070dc963753142bb86c4ed698d91fd623ed28e7 Mon Sep 17 00:00:00 2001
From: ziejd2
Date: Thu, 28 Sep 2017 15:04:40 -0500
Subject: BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02
---
 sourcecodes/bnt-master/HMM/fixed_lag_smoother.m | 65 +++++++++++++++++++++++++
 1 file changed, 65 insertions(+)
 create mode 100644 sourcecodes/bnt-master/HMM/fixed_lag_smoother.m

(limited to 'sourcecodes/bnt-master/HMM/fixed_lag_smoother.m')

diff --git a/sourcecodes/bnt-master/HMM/fixed_lag_smoother.m b/sourcecodes/bnt-master/HMM/fixed_lag_smoother.m
new file mode 100644
index 00000000..9e19df98
--- /dev/null
+++ b/sourcecodes/bnt-master/HMM/fixed_lag_smoother.m
@@ -0,0 +1,65 @@
+function [alpha, obslik, gamma, xi] = fixed_lag_smoother(d, alpha, obslik, obsvec, transmat, act)
+% FIXED_LAG_SMOOTHER Computed smoothed posterior estimates within a window given previous filtered window.
+% [alpha, obslik, gamma, xi] = fixed_lag_smoother(d, alpha, obslik, obsvec, transmat, act)
+%
+% d >= 2 is the desired window width.
+% Actually, we use d=min(d, t0), where t0 is the current time.
+%
+% alpha(:, t0-d:t0-1) - length d window, excluding t0 (Columns indexed 1..d)
+% obslik(:, t0-d:t0-1) - length d window
+% obsvec              - likelihood vector for current observation
+% transmat            - transition matrix
+% If we specify the optional 'act' argument, transmat{a} should be a cell array, and
+% act(t0-d:t0)          - length d window, last column = current action
+%
+% Output:
+% alpha(:, t0-d+1:t0)     - last column = new filtered estimate
+% obslik(:, t0-d+1:t0)    - last column = obsvec
+% xi(:, :, t0-d+1:t0-1)   - 2 slice smoothed window
+% gamma(:, t0-d+1:t0)     - smoothed window
+%
+% As usual, we define (using T=d)
+% alpha(i,t) = Pr(Q(t)=i | Y(1:t))
+% gamma(i,t) = Pr(Q(t)=i | Y(1:T))
+% xi(i,j,t) = Pr(Q(t)=i, Q(t+1)=j | Y(1:T))
+%
+% obslik(i,t) = Pr(Y(t) | Q(t)=i) 
+% transmat{a}(i,j) = Pr(Q(t)=j | Q(t-1)=i, A(t)=a)
+
+[S n] = size(alpha); 
+d = min(d, n+1); 
+if d < 2
+  error('must keep a window of length at least 2');
+end
+
+if ~exist('act')
+  act = ones(1, n+1);
+  transmat = { transmat };
+end
+
+% pluck out last d-1 components from the history
+alpha = alpha(:, n-d+2:n); 
+obslik = obslik(:, n-d+2:n); 
+
+% Extend window by 1
+t = d;
+obslik(:,t) = obsvec;
+xi = zeros(S, S, d-1);
+xi(:,:,t-1) = normalise((alpha(:,t-1) * obslik(:,t)') .* transmat{act(t)});
+alpha(:,t) = sum(xi(:,:,t-1), 1)';
+
+% Now smooth backwards inside the window
+beta = ones(S, d);
+T = d;
+%fprintf('smooth from %d to 1, i.e., %d to %d\n', d, t0, t0-d+1);
+gamma(:,T) = alpha(:,T);
+for t=T-1:-1:1
+  b = beta(:,t+1) .* obslik(:,t+1); 
+  beta(:,t) = normalise(transmat{act(t)} * b);
+  gamma(:,t) = normalise(alpha(:,t) .* beta(:,t));
+  xi(:,:,t) = normalise((transmat{act(t)} .* (alpha(:,t) * b')));
+end
+
+
+
+
-- 
cgit 1.4.1