Code covered by the BSD License  

Highlights from
Hidden Markov Models for Molecular Motors

• DisplayModel(M, L, iterations... Display the HMM described by M, the log likelihood value,
• ForBackF(M,Y) Forward-backward algorithm for step-HMM
• ForwardBackward_3(M,Y,I0,test... function [LL newM gamma] = ForwardBackward_3(M,Y,I0,test,BigB)
• M=MakeMonotonicModel(nu, yQua... function M=MakeMonotonicModel(nu, yQuantum, noiseSigma, transProb, stepSizes, stepSigma)
• ModelChange(M1,M0) Check the changes in the transition probabilities. Looks at the
• PlotAndLabelPeaks(x,y,minsize... function PlotAndLabelPeaks(x,y,minsize,xscale)
• RestorationPlot(Y, EstY, wrap... function RestorationPlot(Y, EstY, wrap, yquantum, EYbase,markerstr) Fancy
• WtConvol(a,b,m)
• [EstY EstI LP Wrap]=ViterbiRe... % Viterbi algorithm for step-HMM
• [X,Y]=StepSimulator(M,N) function [X,Y]=StepSimulator(M,N)
• [X,Y]=StepSimulatorC(M,N) Given the number of time points N and the model M, simulate a staircase
• [sigma nu]=EstSigmaAndNu(Y,I0) Find reasonable values for these variables based on the step data vector
• b=Makeb(nu,sigma,DutyCycle,Er...
• ms=QuickShift(m,shift) Faster replacement for circshift for time-critical applications.
• ms=QuickShiftMex(m,shift) Faster replacement for circshift for time-critical applications.
• n=NextNiceNumber(x,f) function n=NextNiceNumber(x)
• xs=Step125(x)
• MotorHMM1.m
• MotorHMM2.m
• View all files