GDC Document treating about 3d graphics
標簽： Document treating graphics about
上傳時間： 2014-01-13
上傳用戶：gundan
TOYFDTD1 is a stripped-down minimalist, 3D FDTD code demonstrating the basic tasks in implementing a simple 3D FDTD simulation. An idealized rectangular waveguide is modeled by treating the interior of the mesh as free space and enforcing PEC conditions on the faces of the mesh. A simplified plane wave source is inserted at one end. First released 12 April 1999. Version 1.03 released 2 December 1999.
標簽： demonstrating stripped-down implementing minimalist
上傳時間： 2013-12-21
上傳用戶：無聊來刷下
This a very simple Yee algorithm 3D FDTD code in C implementing the free space form of Maxwell s equations on a Cartesian grid. There are no internal materials or geometry. The code as delivered simulates an idealized rectangular waveguide by treating the interior of the mesh as free space/air and enforcing PEC (Perfect Electric Conductor) conditions on the faces of the mesh.
標簽： implementing algorithm Maxwell simple
上傳時間： 2015-05-14
上傳用戶：水中浮云
Using Gaussian elimination to solve linear equations. // In this version, we allow matrix of any size. This is done by treating // the name of a 2-dimensional array as pointer to the beginning of the // array. This makes use of the fact that arrays in C are stored in // row-major order.
標簽： elimination equations Gaussian version
上傳時間： 2016-02-14
上傳用戶：hxy200501
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Package source: sbgcop_0.95.tar.gz MacOS X binary: sbgcop_0.95.tgz Windows binary: sbgcop_0.95.zip Reference manual: sbgcop.pdf
標簽： Semiparametric estimation parameters estimates
上傳時間： 2016-04-15
上傳用戶：talenthn
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Windows binary: sbgcop_0.95.zip
標簽： Semiparametric estimation parameters estimates
上傳時間： 2016-04-15
上傳用戶：qilin
sbgcop: Semiparametric Bayesian Gaussian copula estimation This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data. Version: 0.95 Date: 2007-03-09 Author: Peter Hoff Maintainer: Peter Hoff <hoff at stat.washington.edu> License: GPL Version 2 or later URL: http://www.stat.washington.edu/hoff CRAN checks: sbgcop results Downloads: Reference manual: sbgcop.pdf
標簽： Semiparametric estimation parameters estimates
上傳時間： 2014-12-08
上傳用戶：一諾88
