Author: bugman Date: Thu May 1 14:17:27 2008 New Revision: 6025 URL: http://svn.gna.org/viewcvs/relax?rev=6025&view=rev Log: Shortened the short title of the 'Model-free analysis using the diffusion seeded paradigm' figure. Modified: 1.3/docs/latex/model-free.tex Modified: 1.3/docs/latex/model-free.tex URL: http://svn.gna.org/viewcvs/relax/1.3/docs/latex/model-free.tex?rev=6025&r1=6024&r2=6025&view=diff ============================================================================== --- 1.3/docs/latex/model-free.tex (original) +++ 1.3/docs/latex/model-free.tex Thu May 1 14:17:27 2008 @@ -941,7 +941,7 @@ % The diffusion seeded paradigm figure. \begin{figure} \centerline{\includegraphics[width=0.8\textwidth, bb=0 0 437 523]{images/model_free/init_diff_est.eps.gz}} -\caption[Model-free analysis using the diffusion seeded paradigm -- the initial diffusion tensor estimate]{A schematic of model-free analysis using the diffusion seeded paradigm -- the initial diffusion tensor estimate -- together with AIC model selection and model elimination. The initial estimates of the parameters of $\Diffset$ are held constant while model-free models $m0$ to $m9$ (\ref{model: m0}--\ref{model: m9}) of the set $\Mfset_i$ for each spin system $i$ are optimised, model elimination applied to remove failed models, and AIC model selection used to determine the best model. The global model $\Space$, the union of $\Diffset$ and all $\Mfset_i$, is then optimised. These steps are repeated until convergence of the global model. The entire iterative process is repeated for each of the Brownian diffusion models. Finally AIC model selection is used to determine the best description of the dynamics of the molecule by selecting between the global models $\Space$ including the sphere, oblate spheroid, prolate spheroid, and ellipsoid. Once the solution has been found, Monte Carlo simulations can be utilised for error analysis.} \label{fig: init diff estimate} +\caption[Model-free analysis using the diffusion seeded paradigm]{A schematic of model-free analysis using the diffusion seeded paradigm -- the initial diffusion tensor estimate -- together with AIC model selection and model elimination. The initial estimates of the parameters of $\Diffset$ are held constant while model-free models $m0$ to $m9$ (\ref{model: m0}--\ref{model: m9}) of the set $\Mfset_i$ for each spin system $i$ are optimised, model elimination applied to remove failed models, and AIC model selection used to determine the best model. The global model $\Space$, the union of $\Diffset$ and all $\Mfset_i$, is then optimised. These steps are repeated until convergence of the global model. The entire iterative process is repeated for each of the Brownian diffusion models. Finally AIC model selection is used to determine the best description of the dynamics of the molecule by selecting between the global models $\Space$ including the sphere, oblate spheroid, prolate spheroid, and ellipsoid. Once the solution has been found, Monte Carlo simulations can be utilised for error analysis.} \label{fig: init diff estimate} \end{figure}