This GUI can be used by entering nu at the MATLAB command prompt. The user can either select a function (f(x)) of their choice or a statistical distribution probability distribution function to plot over a user defined range. The function s integral can be evaluated over a user defined range by using: The composite trapezium, simpsons and gauss-legendre rules. This is useful for calculating accurate probabilities that one might see in statistical tables.
Will perform 3D Gaussian quadrature over a user-defined volume. The volume is defined by the user with function definitions entered in the appropriate spaces provided on the GUI. The user can change the number of Gauss points to use.
Function inputs need not accept vector args.
This function calculates Akaike s final prediction error
％ estimate of the average generalization error.
％
％ [FPE,deff,varest,H] = fpe(NetDef,W1,W2,PHI,Y,trparms) produces the
％ final prediction error estimate (fpe), the effective number of
％ weights in the network if the network has been trained with
％ weight decay, an estimate of the noise variance, and the Gauss-Newton
％ Hessian.
％
This function calculates Akaike s final prediction error
％ estimate of the average generalization error for network
％ models generated by NNARX, NNOE, NNARMAX1+2, or their recursive
％ counterparts.
％
％ [FPE,deff,varest,H] = nnfpe(method,NetDef,W1,W2,U,Y,NN,trparms,skip,Chat)
％ produces the final prediction error estimate (fpe), the effective number
％ of weights in the network if it has been trained with weight decay,
％ an estimate of the noise variance, and the Gauss-Newton Hessian.
％
