Computes estimates for the number of forests of a graph, input as a 0-1 incidence matrix. Notes: Compile in C++, "g++ -o span_forest span_forest.c". The program does not demand that the matrix is symmetric with 0 diagonal, but uses only the upper triangular part.
標簽： estimates incidence Computes forests
上傳時間： 2013-12-26
上傳用戶：com1com2
Optimal Spatial Regelarisation of Autocorrelation estimates in fMRI Analysis,very useful,if you like you can download it.
標簽： Autocorrelation Regelarisation estimates Analysis
上傳時間： 2015-11-05
上傳用戶：TRIFCT
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
Accurate estimates of the autocorrelation or power spectrum can be obtained with a parametric model (AR, MA or ARMA). With automatic inference, not only the model parameters but also the model structure are determined from the data. It is assumed that the ARMASA toolbox is presen
標簽： autocorrelation parametric estimates Accurate
上傳時間： 2013-12-29
上傳用戶：3到15
基于現代譜估計方法的間諧波檢測Spectrum estimates based on modern methods of detection of harmonic
標簽： estimates detection Spectrum harmonic
上傳時間： 2014-12-20
上傳用戶：qiaoyue
Description The MUSIC algorithm, proposed by Schmidt, first estimates a basis for the noise subspace and then determines the peaks the associated angles provide the DOA estimates. The MATLAB code for the MUSIC algorithm is sampled by creating an array of steering vectors corresponding to the angles in the vector angles.
標簽： Description algorithm estimates proposed
上傳時間： 2013-12-08
上傳用戶：hgy9473
a new method for identification of fast fading mobile channels. estimates both the channel statistics and the time varying channel impulse respone on -line.
標簽： identification estimates statistic channels
上傳時間： 2014-12-22
上傳用戶：lz4v4
The Kalman filter is an efficient recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering applications from radar to computer vision, and is an important topic in control theory and control systems engineering. Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear-quadratic-Gaussian control problem (LQG). The Kalman filter, the linear-quadratic regulator and the linear-quadratic-Gaussian controller are solutions to what probably are the most fundamental problems in control theory.
標簽： filter efficient estimates recursive
上傳時間： 2017-08-06
上傳用戶：風之驕子
