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• Maximum likelihood estimator
  ... ne through unconstrained nonlinear programming algorithm using first-order gradient, such as the [[steepest descent]] method, [[BHHH]] and [[BFGS method | BFG ... :At the maximum likelihood, the gradient of the log-likelihood equals zero: '''''g''(''θ'')=0'''. The asymptotic d ...
  3 KB (396 words) - 00:00, 1 February 2008
• Publications
  # Khajavirad, A. and J.J. Michalek (2007) "A single-stage gradient-based approach for solving the joint product family platform selection and ...
  7 KB (1014 words) - 21:28, 25 January 2008
• Steepest descent
  ... ion along that gradient direction, settles on the global minima along that gradient direction, and sets the next point to that global minima. The user then c ... ... that specific point which defines how much we move in the direction of the gradient to approach the new point of independent variables <math> f(\mathbf{x}_{i+ ...
  5 KB (781 words) - 00:31, 27 December 2006
• Nash equilibrium
  ... fact makes it solvable by basic numerical [[gradient based methods]] or [[gradient free methods]]. Both methods require that two conditions are met by the pa ... ... at <math> \nabla p = \frac{\partial{p}}{\partial{\mathbf{s}}} </math> (the gradient of the payoff function) is zero for identification of a critical point.
  6 KB (841 words) - 14:56, 9 May 2008
• Optimization
  ... satisfied only at certain special points in the space, and the function [[gradient]]s can be used to search for such points. In contrast, integer variables a ... ... ints in the entire space). Because of this, algorithms that use function [[gradient]]s to move downhill toward a local solution will eventually arrive at the ...
  11 KB (1531 words) - 22:04, 17 November 2010
• Coevolutionary algorithms
  ... t simply nothing can be learned by either population by competing. Loss of gradient is not strictly a competitive CEA problem, though. In a more general setti ...
  12 KB (1827 words) - 15:56, 11 January 2007
• Downhill simplex
  ... value is replaced by a point that occurs in the direction of the steepest gradient. This is an efficient way for the simplex to move toward lower values.
  4 KB (671 words) - 17:56, 12 February 2008
• Lagrange multipliers
  ... re saying that the gradient of the function (always points uphill) and the gradient of the constraint (always perpendicular to the constraint) are parallel to ... ... e treated as if it were an unconstrained function of n+k variables. If the gradient of the Langrangian is zero and the Hessian of the Lagrangian is positive d ...
  2 KB (314 words) - 18:08, 11 January 2007
• Paintball marker
  ... || '''1.''' Direct ball after exiting marker <br/> '''2.''' Cause pressure gradient decreasing paintball deformation <br/> '''3.''' Unscrews for easy cleaning ...
  31 KB (5100 words) - 21:28, 12 September 2007
• MINOS
  #Nonlinear objective function with linear constraints: MINOS uses reduced-gradient method to generate search direction.
  1 KB (188 words) - 19:21, 18 March 2007
• BFGS method
  ... imate Hessian matrix. Avoiding the calculation of exact Hessian (2nd-order gradient) can save significant computational cost during iteration process of optim ...
  2 KB (227 words) - 17:47, 23 September 2007
• Introduction to random utility discrete choice models
  To find the maximum by hand, we can take the gradient of the function, set it equal to zero, solve the resulting system of equat ...
  34 KB (5423 words) - 01:24, 15 March 2010
• Convex nonlinear programming
  * [[Generalized reduced gradient]] ***'''Linearly constrainted nonlinear program:''' [[Reduced gradient]] method combined with a [[quasi-newton]] algorithm
  4 KB (602 words) - 21:15, 27 October 2008
• Doughnut maker
  ... tant temperature. We may vary this temperature to observe how the thermal gradient develops inside the doughnut over time. ... he calculations while gaining a good perspective on the developing thermal gradient. Therefore, this model will be constructed of a circular cross section sw ...
  79 KB (11950 words) - 20:39, 8 October 2009
• Taylor series
  where <math>\nabla f(\mathbf{x}_0)\!</math> is the [[gradient]] of <math>\,f</math> evaluated at <math>\mathbf{x} = \mathbf{x}_0</math> ...
  1 KB (232 words) - 20:44, 20 January 2010
• Snowboard opportunity
  # Goggles with edge detection and colored terrain gradient # Screen on board showing speed, gradient, time
  46 KB (7280 words) - 05:05, 28 February 2012
• Iron
  ... pump and a compression spring. When the steam button is pressed a pressure gradient is created and the water is pushed up and out into a tube that leads to a ...
  45 KB (7059 words) - 03:58, 25 September 2012

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