# Guided Training

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For example, suppose you are interested in estimating a general irreversible rate matrix. You might start by estimating a matrix of the form $R_{ij} = \kappa \pi_j$ (called the "rind" model in xgram), where rates in each column are constrained to be identical. Next, you would estimate a general reversible model using the previous "rind" model as a seed (note that reversible models satisfy the constraint $\pi_i R_{ij} = \pi_j R_{ji}$, which is slightly weaker than the "rind" constraint). Finally, you would use this reversible matrix as a seed to estimate the general irreversible model (unconstrained except for the general rate matrix constraints $\sum_j R_{ij}=0$ and $\sum_i \pi_i = 1$).