FitExpectationMaximization: Expectation-Maximization (EM) algorithm to recover missing...
In R-Finance/Meucci: Collection of functionality ported from the MATLAB code of Attilio Meucci.
Description
Usage
Arguments
Value
Author(s)
References
Description
Expectation-Maximization (EM) algorithm to recover
missing observations in a time series , as described in
A. Meucci, "Risk and Asset Allocation", Springer, 2005,
section 4.6.2 "Missing data".
Usage
1
Arguments
X
: [matrix] (T x N) of data
Value
E_EM : [vector] (N x 1) expectation
S_EM : [matrix] (N x N) covariance matrix
Y : [matrix] (T x N) updated data
CountLoop : [scalar] number of iterations of the
algorithm
Author(s)
Xavier Valls flamejat@gmail.com
References
A. Meucci - "Exercises in Advanced Risk and Portfolio
Management" http://symmys.com/node/170, "E 177 -
Expectation-Maximization algorithm for missing data:
formulas" See Meucci's script for
"FitExpectationMaximization.m"
Dempster, A. P. and Laird, M. N. and Rubin, D. B. -
"Maximum Likelihood from Incomplete Data Via the EM
Algorithm", Journal of the Royal Statistical Society,
1977 vol 39 pag. 1-22.
Bilmes, J. A.- "A Gentle Tutorial of the EM Algorithm and
its Application to Parameter Estimation for Gaussian
Mixture and Hidden Markov Models", 1998.
R-Finance/Meucci documentation built on May 8, 2019, 3:52 a.m.
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Description Usage Arguments Value Author(s) References
Description
Expectation-Maximization (EM) algorithm to recover missing observations in a time series , as described in A. Meucci, "Risk and Asset Allocation", Springer, 2005, section 4.6.2 "Missing data".
Usage
1 |
Arguments
X |
: [matrix] (T x N) of data |
Value
E_EM : [vector] (N x 1) expectation
S_EM : [matrix] (N x N) covariance matrix
Y : [matrix] (T x N) updated data
CountLoop : [scalar] number of iterations of the algorithm
Author(s)
Xavier Valls flamejat@gmail.com
References
A. Meucci - "Exercises in Advanced Risk and Portfolio Management" http://symmys.com/node/170, "E 177 - Expectation-Maximization algorithm for missing data: formulas" See Meucci's script for "FitExpectationMaximization.m"
Dempster, A. P. and Laird, M. N. and Rubin, D. B. - "Maximum Likelihood from Incomplete Data Via the EM Algorithm", Journal of the Royal Statistical Society, 1977 vol 39 pag. 1-22.
Bilmes, J. A.- "A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models", 1998.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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