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.
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
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
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
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
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.
a new method for identification of fast fading mobile channels. estimates both the channel statistics and the time varying channel impulse respone on -line.
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.
