Before specifying'VarNames',varNames, you can verify the variable names invarNamesby using theisvarnamefunction. If the variable names are not valid, then you can convert them by using thematlab.lang.makeValidNamefunction. Example:'VarNames',{'Horsepower','Acceleration','Model_Year','MPG'} ...
penalized optimization problemlogarithmic penalty functioninvex functionCourant-Beltrami penalty functionIn this paper, we have reviewed some penalty function methods for solving constrained optimization problems in the literature and proposed a continuously differentiable logarith- mic penalty function which ...
Before specifying 'VarNames',varNames, you can verify the variable names in varNames by using the isvarname function. If the variable names are not valid, then you can convert them by using the matlab.lang.makeValidName function. Example: 'VarNames',{'Horsepower','Acceleration','Model_Year'...
This MATLAB function returns penalized, maximum-likelihood fitted coefficients for generalized linear models of the predictor data X and the response y, where the values in y are assumed to have a normal probability distribution.
Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares ...
However, as indicated in the discussion of (2.16), when Jfd contains a term Rfd(y) penalizing y over Ω1 exactly as x is penalized over Ω0 in Rfd(x), the asymmetry in (3.34) and (3.35) disappears, albeit with considerable cost in complexity of the formulation. On the other hand...
Model-based penalized regressionOrdinary differential equations (ODEs) are equalities involving a function and its derivatives that define the evolution of the function over a pre-specified domain. The applications of ODEs range from simulation and prediction to control and diagnosis in diverse fields ...
Finally, we verify numerically this result and we show the convenience of the proposed SIMP-ALL interpolation for obtaining auto-penalized optimal design in a wider range of cases. A MATLAB code of the SIMP-ALL interpolation function is also provided....
In Matlab environment, the generic Riemannian trust-region package for the optimization of functions defined on Riemannian manifolds is available at: http://www.math.fsu.edu/~cbaker/GenRTR/. Because the general RTR method proposed in [4, 5] is stated to minimize a cost function on a general...