We introduce GGLasso, a Python package for solving General Graphical Lasso problems. The scheme, introduced by (Friedman 2007) (see also (Yuan 2007; Banerjee 2008)), estimates sparse inverse covariance matrix $\Theta$ from multivariate Gaussian data $\mathcal{X} \sim \mathcal{N}(\mu, \Sigma) \in \mathbb{R}^p$. Originally proposed (Dempster 1972) under the name Covariance Selection, this estimat...

This article intends to estimate the optimal value of investment and human capital in R&D sector of Iranian economy using an augmented endogenous growth model. To do so, two issues have been studied. First, an endogenous growth model has been extended to include investment in R&D as an independent variable. In the framework of this model, in order to determine the optimal value of investment an...

In this paper, with the aim of estimating internal dynamics matrix of a gimbaled Inertial Navigation system (as a discrete Linear system), the discretetime Hamilton-Jacobi-Bellman (HJB) equation for optimal control has been extracted. Heuristic Dynamic Programming algorithm (HDP) for solving equation has been presented and then a neural network approximation for cost function and control input ...

this paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. this estimation method is obtained by implementing ridge regression learning algorithm in the la- grangian dual space. the distance measure for fuzzy numbers that suggested by diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...

Hough transform and snakes methods retrieve straight lines and distorted contours but present limitations. In this paper, fast high resolution methods are adapted to multiple contour estimation. Distorted contours are retrieved with a novel optimization method. 2007 Elsevier B.V. All rights reserved. PACS: 42.65.R; 42.30.T; 07.05.P; 42.30.W; 42.30.S

in this paper, we consider admissible estimation of the parameter ?r in the gamma distribution with truncated parameter space under entropy loss function. we obtain the classes of admissible estimators. the result can be applied to estimation of parameters in the normal, lognormal, pareto, generalized gamma, generalized laplace and other distributions.

Bayesian D-optimal designs supported on a xed number of points were found by Dette and Wong (1998) for estimating parameters in a polynomial model when the error variance depends exponentially on the explanatory variable. This work provides optimal designs under a broader class of error variance structures and investigates the robustness properties of these designs to model and prior distributi...

Optimal control problems in batch distillation involve finding a trajectory for the reflux ratio so as to maximize a performance index. Then the controller is asked to follow this trajectory in an open loop fashion. It is important to minimize the effect of uncertainties in thermodynamic models on the optimal control profiles to achieve a better operating performance. The non-linear parameter e...