If that file is not present, then you should try to reinstall the MATLAB. The correct file should be located at C:\Program Files\MATLAB\R2020a\toolbox\optim\optim\getIpOptions.m. As Walter mentioned, the file you showed is the run-time version of getIpOptions.m. p polyfit (x,y,7) Evaluate the polynomial on a finer grid and plot the results. and the rest of the code can also be seen. options optimoptions ( 'fminunc', 'Algorithm', 'quasi-newton' ) View the iterations as the solver performs its calculations. This step ensures that the tutorial works the same in every MATLAB version. x0 -.5 0 Set optimization options to use the fminunc default 'quasi-newton' algorithm. x linspace (0,4pi,10) y sin (x) Use polyfit to fit a 7th-degree polynomial to the points. Set an initial point for finding the solution. Generate 10 points equally spaced along a sine curve in the interval 0,4pi. outcomeCounts ( 2 )/ nTrials ( cc ) end for cc = 1 : length ( stimCounts ) h = scatter ( stim ( cc ), pCorrect ( cc ), 100, 'o', 'MarkerEdgeColor', 'MarkerFaceColor' . Fit Polynomial to Trigonometric Function. The original BADS paper was presented at NeurIPS in 2017. The toolbox enables the efficient implementation of the updated maximum-likelihood (UML) procedure. BADS is a fast hybrid Bayesian optimization algorithm designed to solve difficult optimization problems, in particular related to fitting computational models (e.g., via maximum likelihood estimation). For this problem the estimator is the Maximum Likelihood Estimator (MLE) and. A MATLAB toolbox for the efficient estimation of the threshold, slope, and lapse rate of the psychometric function is described. outcomeCounts ) pCorrect ( cc ) = stimCounts ( cc ). Template for parameter estimation with Matlab Optimization Toolbox. %% Plot of trial locations with maximum likelihood fit figure clf hold on stimCounts = qpCounts ( qpData ( trialData ), nOutcomes ) stim = stimFine = linspace ( - 40, 0, 100 ) ' plotProportionsFit = qpPFWeibull ( stimFine, psiParamsFit ) for cc = 1 : length ( stimCounts ) nTrials ( cc ) = sum ( stimCounts ( cc ). REML estimation is implemented in Surfstat, a Matlab toolbox for the statistical analysis of univariate and multivariate surface and volumetric neuroimaging.
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