networkTomography implements the methods developed and evaluated in Blocker and Airoldi (2011) and Airoldi and Blocker (2012). These include the authors' own dynamic multilevel model with calibration based upon a Gaussian state-space model in addition to implementations of the methods of Tebaldi & West (1998; Poisson-Gamma model with MCMC sampling), Zhang et al. (2002; tomogravity), Cao et al. (2000; Gaussian model with mean-variance relation), and Vardi (1996; method of moments). Data from the 1router network of Cao et al. (2000), the Abilene network of Fang et al. (2007), and the CMU network of Blocker and Airoldi (2011) are included for testing and reproducibility.

Author | Alexander W Blocker, Paul Koullick, Edoardo Airoldi |

Date of publication | 2014-01-10 07:28:23 |

Maintainer | Alexander W Blocker <ablocker@gmail.com> |

License | LGPL-2 |

Version | 0.3 |

https://github.com/awblocker/networkTomography |

**abilene:** Abilene data from Fang et al. (2007)

**agg:** Function to aggregate results from matrix to matrix

**bayesianDynamicFilter:** Function for inference with multilevel state-space model

**bell.labs:** Bell Labs 1router data from Cao et al. (2000)

**buildPrior:** Construct prior from calibration model estimates

**buildRoutingMat:** Build routing matrices for linked star topologies; that is, a...

**buildRoutingMatrix:** Build routing matrix from table of link relationships

**buildStarMat:** Build routing matrix for star network topology

**calcN:** Compute total traffic from a particular time.

**calibration_ssm:** Estimation for the linear SSM calibration model of Blocker &...

**cmu:** CMU data from Blocker & Airoldi (2011)

**decomposeA:** Compute pivoted decomposition of routing matrix A into...

**diag_ind:** Make vector of 1-dimensional diagonal indices for square...

**diag_mat:** Make diagonal matrix from vector

**dobj.dxt.tomogravity:** Analytic gradient of objective function of Zhang et al. 2003

**getActive:** Check for deterministically-known OD flows at single time

**getSrcDstIndices:** Find indices of source and destination for each...

**grad_iid:** Compute analytic gradient of Q-function for locally IID EM...

**grad_smoothed:** Compute analytic gradient of Q-function for smoothed EM...

**gravity:** Run tomogravity estimation on complete time series of...

**gravity.fit:** Gravity estimation for a single time point

**ipfp:** Function to run basic IPFP (iterative proportional fitting...

**llCalibration:** Evaluate marginal log-likelihood for calibration SSM

**locally_iid_EM:** Run EM algorithm to obtain MLE for locally IID model of Cao...

**m_estep:** Compute conditional expectations for EM algorithms of Cao et...

**mle_filter:** Filtering & smoothing at MLE for calibration SSM

**move_step:** Move step of sample-resample-move algorithm for multilevel...

**obj.tomogravity:** Objective function of Zhang et al. 2003

**phi_init:** Simple initialization for phi in model of Cao et al. (2000)

**Q_iid:** Q function for locally IID EM algorithm of Cao et al. (2000)

**Q_smoothed:** Q function for smoothed EM algorithm of Cao et al. (2000)

**R_estep:** Compute conditional covariance matrix for EM algorithms of...

**smoothed_EM:** Run EM algorithm to obtain MLE (single time) for smoothed...

**strphour:** Convert time string to decimal hour

**thin:** Thinning vector of indices for MCMC

**tomogravity:** Run tomogravity estimation on complete time series of...

**tomogravity.fit:** Tomogravity estimation for a single time point using L-BFGS-B

**twMCMC:** Function to run MCMC sampling for model of Tebaldi & West...

**vardi.algorithm:** Run algorithm of Vardi (1996) given B and S matrices

**vardi.compute.BS:** Compute B and S matrices in algorithm of Vardi (1996)

**vardi.iteration:** Execute single iteration for algorithm of Vardi (1996)

networkTomography

networkTomography/src

networkTomography/src/Makevars

networkTomography/src/Makevars.win

networkTomography/src/ipfp.c

networkTomography/NAMESPACE

networkTomography/data

networkTomography/data/cmu.rda

networkTomography/data/abilene.rda

networkTomography/data/bell.labs.rda

networkTomography/R

networkTomography/R/parseTopology.R
networkTomography/R/caoEtAl.R
networkTomography/R/twMCMC.R
networkTomography/R/ssmMle.R
networkTomography/R/data.R
networkTomography/R/ipfp.R
networkTomography/R/tomogravity.R
networkTomography/R/ssmMCMC.R
networkTomography/R/lib.R
networkTomography/R/vardi.algorithm.R
networkTomography/R/gravity.R
networkTomography/R/imports.R
networkTomography/README.md

networkTomography/MD5

networkTomography/DESCRIPTION

networkTomography/man

networkTomography/man/gravity.fit.Rd
networkTomography/man/buildRoutingMat.Rd
networkTomography/man/strphour.Rd
networkTomography/man/Q_iid.Rd
networkTomography/man/diag_mat.Rd
networkTomography/man/gravity.Rd
networkTomography/man/tomogravity.fit.Rd
networkTomography/man/buildRoutingMatrix.Rd
networkTomography/man/llCalibration.Rd
networkTomography/man/dobj.dxt.tomogravity.Rd
networkTomography/man/m_estep.Rd
networkTomography/man/calibration_ssm.Rd
networkTomography/man/Q_smoothed.Rd
networkTomography/man/tomogravity.Rd
networkTomography/man/grad_iid.Rd
networkTomography/man/vardi.iteration.Rd
networkTomography/man/R_estep.Rd
networkTomography/man/move_step.Rd
networkTomography/man/smoothed_EM.Rd
networkTomography/man/getSrcDstIndices.Rd
networkTomography/man/twMCMC.Rd
networkTomography/man/ipfp.Rd
networkTomography/man/bell.labs.Rd
networkTomography/man/bayesianDynamicFilter.Rd
networkTomography/man/getActive.Rd
networkTomography/man/diag_ind.Rd
networkTomography/man/calcN.Rd
networkTomography/man/locally_iid_EM.Rd
networkTomography/man/agg.Rd
networkTomography/man/thin.Rd
networkTomography/man/obj.tomogravity.Rd
networkTomography/man/cmu.Rd
networkTomography/man/phi_init.Rd
networkTomography/man/mle_filter.Rd
networkTomography/man/decomposeA.Rd
networkTomography/man/grad_smoothed.Rd
networkTomography/man/vardi.algorithm.Rd
networkTomography/man/buildStarMat.Rd
networkTomography/man/abilene.Rd
networkTomography/man/buildPrior.Rd
networkTomography/man/vardi.compute.BS.Rd
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