# The arboretum procedure

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 : documentationdocumentation -> From cyber-crime to insider trading, digital investigators are increasingly being asked todocumentation -> EnCase Forensic Transform Your Investigationsdocumentation -> File Sharing Documentation Prepared by Alan Halter Created: 1/7/2016 Modified: 1/7/2016documentation -> Gaia Data Release 1 Documentation release 0 The DMREG Procedure NLOPTIONS Statement Specifies options for nonlinear optimizations. These options only apply to logistic regression models. NLOPTIONS nonlinear-option(s); Nonlinear-Options ABSCONV= number Specifies an absolute function convergence criterion. ABSCONV= is a function of the log-likelihood for the intercept-only model. The optimization is to maximize the log-likelihood. Default:__Range:___number'>Default: The default value is 1e-3 times the log-likelihood of the null model (intercept-only model). Range: number > 0 ABSFCONV= number Specifies an absolute function convergence criterion. Default:  times the log-likelihood of the intercept-only model Range: number > 0 ABSGCONV= number Specifies the absolute gradient convergence criterion. Default: 1E-5 Range: number > 0 ABSXCONV= number Specifies the absolute parameter convergence criterion. Default: 1E-8 Range: number > 0 DAMPSTEP= number Specifies that the initial step size value for each line search used by the QUANEW, CONGRA, or NEWRAP techniques cannot be larger than the product of number and the step size value used in the previous iteration. Default: 2 Range: number > 0 DIAHES Forces the optimization algorithm (TRUREG, NEWRAP, or NRRIDG) to take advantage of the diagonality. FCONV= number Specifies a function convergence criterion. Default: , where FDIGITS is the value of the FDIGITS= option. Range: number > 0 FCONV2= number Specifies another function convergence criterion. Default: Range: number > 0 FDIGITS= number Specifies the number of accurate digits in evaluations of the objective function. Default: , where   is the machine precision. Range: number > 0 FSIZE= number Specifies the parameter of the relative function and relative gradient termination criteria. Default: 0 Range: number   0 GCONV= number Specifies the relative gradient convergence criterion. Default: Range: number > 0 GCONV2= number Specifies another relative gradient convergence criterion. Default: 0 Range: number > 0 HESCAL= 0 | 1 | 2 |3 Specifies the scaling version of the Hessian or cross-product Jacobian matrix used in NRRIDG, TRUREG, LEVMAR, NEWRAP, or DBLDOG optimization. Default: 1 - for LEVMAR minimization technique 0 - for all others INHESSIAN= number Specifies how to define the initial estimate of the approximate Hessian for the quasi-Newton techniques QUANEW and DBLDOG. Range: number   0 Default: The default is to use a Hessian based on the initial estimates as the initial estimate of the approximate Hessian. When r=0, the initial estimate of the approximate Hessian is computed from the magnitude of the initial gradient. INSTEP= number Specifies a larger or smaller radius of the trust region used in the TRUREG, DBLDOG, and LEVMAR algorithms. Default: 1 Range: number > 0 LINESEARCH= number Specifies the line-search method for the CONGRA, QUANEW, and NEWRAP optimization techniques. Default: 2 Range: 1   number   8 LSPRECISION= number Specifies the degree of accuracy that should be obtained by the second and third line-search algorithms. Default: Table of Line-Search Precision Values TECHNIQUE= UPDATE= LSPRECISION VALUE QUANEW DBFGS, BFGS 0.4 QUANEW DDFP, DFP 0.06 CONGRA all 0.1 NEWRAP no update 0.9 Range: number > 0 MAXFUNC= number Specifies the maximum number of function calls in the optimization process. The objective function that is minimized is the negative log-likelihood. Default: 125 for TRUREG, NRRIDG, and NEWRAP. 500 for QUANEW and DBLDOG. 1000 for CONGRA. Range: number > 0 MAXITER= number Specifies the maximum number of iterations in the optimization process. Default: 50 for TRUREG, NRRIDG and NEWRAP 200 for QUANEW and DBLDOG 400 for CONGRA Range: number > 0 MAXSTEP= number Specifies the upper bound for the step length of the line-search algorithms. Default: Range: number > 0 Dostları ilə paylaş:

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