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**ergm**: Fit, Simulate and Diagnose Exponential-Family Models for Networks**g4**: Goodreau's four node network as a "network" object

# Goodreau's four node network as a “network" object

### Description

This is an example thought of by Steve Goodreau. It is a directed
network of four nodes and five ties stored as a `network`

object.

It is interesting because the maximum likelihood estimator of the model with out degree 3 in it exists, but the maximum psuedolikelihood estimator does not.

### Usage

1 |

### Source

Steve Goodreau

### See Also

florentine, network, plot.network, ergm

### Examples

1 2 3 |

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- anova.ergm: ANOVA for ERGM Fits
- anova.ergm: ANOVA for ERGM Fits
- approx.hotelling.diff.test: Approximate Hotelling T^2-Test for One Sample Means
- approx.hotelling.diff.test: Approximate Hotelling T^2-Test for One Sample Means
- as.edgelist: Convert a network object into a numeric edgelist matrix
- as.edgelist: Convert a network object into a numeric edgelist matrix
- as.network.numeric: Create a Simple Random network of a Given Size
- as.network.numeric: Create a Simple Random network of a Given Size
- check.ErgmTerm: Ensures an Ergm Term and its Arguments Meet Appropriate...
- check.ErgmTerm: Ensures an Ergm Term and its Arguments Meet Appropriate...
- coef.ergm: Extract Model Coefficients
- coef.ergm: Extract Model Coefficients
- coef.length.model: Extract Number of parameters in ergm Model
- control.ergm: Auxiliary for Controlling ERGM Fitting
- control.ergm: Auxiliary for Controlling ERGM Fitting
- control.ergm.bridge: Auxiliary for Controlling ergm.bridge
- control.ergm.bridge: Auxiliary for Controlling ergm.bridge
- control.gof: Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation
- control.gof: Auxiliary for Controlling ERGM Goodness-of-Fit Evaluation
- control.logLik.ergm: Auxiliary for Controlling logLik.ergm
- control.logLik.ergm: Auxiliary for Controlling logLik.ergm
- control.san: Auxiliary for Controlling SAN
- control.san: Auxiliary for Controlling SAN
- control.simulate.ergm: Auxiliary for Controlling ERGM Simulation
- control.simulate.ergm: Auxiliary for Controlling ERGM Simulation
- degreedist: Computes and Returns the Degree Distribution Information for...
- degreedist: Computes and Returns the Degree Distribution Information for...
- ecoli: Two versions of an E. Coli network dataset
- ecoli: Two versions of an E. Coli network dataset
- enformulate.curved: Convert a curved ERGM into a form suitable as initial values...
- enformulate.curved: Convert a curved ERGM into a form suitable as initial values...
- ergm: Exponential-Family Random Graph Models
- ergm: Exponential-Family Random Graph Models
- ergm.allstats: Calculate all possible vectors of statistics on a network for...
- ergm.allstats: Calculate all possible vectors of statistics on a network for...
- ergm.bounddeg: initializes the parameters to bound degree during sampling
- ergm.bounddeg: initializes the parameters to bound degree during sampling
- ergm.bridge.dindstart.llk: Bridge sampling to estiamte log-likelihood of an ERGM, using...
- ergm.bridge.dindstart.llk: Bridge sampling to estiamte log-likelihood of an ERGM, using...
- ergm.bridge.llr: A simple implementation of bridge sampling to evaluate...
- ergm.bridge.llr: A simple implementation of bridge sampling to evaluate...
- ergm.ConstraintImplication: Set up the implied constraints from the current constraint
- ergm.ConstraintImplication: Set up the implied constraints from the current constraint
- ergm-constraints: Sample Space Constraints for Exponential-Family Random Graph...
- ergm-constraints: Sample Space Constraints for Exponential-Family Random Graph...
- ergm.Cprepare: Internal Function to Prepare Data for ergm's C Interface
- ergm.Cprepare: Internal Function to Prepare Data for ergm's C Interface
- ergm.degeneracy: Checks an ergm Object for Degeneracy
- ergm.degeneracy: Checks an ergm Object for Degeneracy
- ergm_deprecated: Functions that will no longer be supported in future releases...
- ergm_deprecated: Functions that will no longer be supported in future releases...
- ergm.eta: Operations with 'eta' vector of canonical parameter values...
- ergm.eta: Operations with 'eta' vector of canonical parameter values...
- ergm.exact: Calculate the exact loglikelihood for an ERGM
- ergm.exact: Calculate the exact loglikelihood for an ERGM
- ergm_formula_utils: Internal Functions for Querying, Validating and Extracting...
- ergm_formula_utils: Internal Functions for Querying, Validating and Extracting...
- ergm.geodistdist: calculate geodesic distance distribution for a network or...
- ergm.geodistdist: calculate geodesic distance distribution for a network or...
- ergm.getglobalstats: internal function to return global statistics for a given...
- ergm.getglobalstats: internal function to return global statistics for a given...
- ergm.getMCMCsample: Internal Function to Sample Networks Using C Wrapper
- ergm.getMCMCsample: Internal Function to Sample Networks Using C Wrapper
- ergm.init.methods: Set up the initial fitting methods for reference measure and...
- ergm.init.methods: Set up the initial fitting methods for reference measure and...
- ergm-internal: Internal ergm Objects
- ergm-internal: Internal ergm Objects
- ergm-MetropolisHastingsProposals: Metropolis-Hastings Proposal Methods for ERGM MCMC
- ergm-MetropolisHastingsProposals: Metropolis-Hastings Proposal Methods for ERGM MCMC
- ergm.MHP.table: Table mapping reference,constraints, etc. to Metropolis...
- ergm.mple: Find a maximizer to the psuedolikelihood function
- ergm.mple: Find a maximizer to the psuedolikelihood function
- ergmMPLE: ERGM Predictors and response for logistic regression...
- ergmMPLE: ERGM Predictors and response for logistic regression...
- ergm-package: Fit, Simulate and Diagnose Exponential-Family Models for...
- ergm-package: Fit, Simulate and Diagnose Exponential-Family Models for...
- ergm-parallel: Parallel Processing in the 'ergm' Package
- ergm-parallel: Parallel Processing in the 'ergm' Package
- ergm-references: Reference Measures for Exponential-Family Random Graph Models
- ergm-references: Reference Measures for Exponential-Family Random Graph Models
- ergm-terms: Terms used in Exponential Family Random Graph Models
- ergm-terms: Terms used in Exponential Family Random Graph Models
- eut-upgrade: Updating 'ergm.userterms' prior to 3.1
- eut-upgrade: Updating 'ergm.userterms' prior to 3.1
- faux.desert.high: Faux desert High School as a network object
- faux.desert.high: Faux desert High School as a network object
- faux.dixon.high: Faux dixon High School as a network object
- faux.dixon.high: Faux dixon High School as a network object
- faux.magnolia.high: Goodreau's Faux Magnolia High School as a network object
- faux.magnolia.high: Goodreau's Faux Magnolia High School as a network object
- faux.mesa.high: Goodreau's Faux Mesa High School as a network object
- faux.mesa.high: Goodreau's Faux Mesa High School as a network object
- fix.curved: Convert a curved ERGM into a corresponding "fixed" ERGM.
- fix.curved: Convert a curved ERGM into a corresponding "fixed" ERGM.
- flobusiness: Florentine Family Business Ties Data as a "network" object
- flobusiness: Florentine Family Business Ties Data as a "network" object
- flomarriage: Florentine Family Marriage Ties Data as a "network" object
- flomarriage: Florentine Family Marriage Ties Data as a "network" object
- florentine: Florentine Family Marriage and Business Ties Data as a...
- florentine: Florentine Family Marriage and Business Ties Data as a...
- g4: Goodreau's four node network as a "network" object
- g4: Goodreau's four node network as a "network" object
- get.free.dyads: Create a network containing only edges meeting a specific...
- get.node.attr: Retrieve and check assumptions about vertex attributes (nodal...
- get.node.attr: Retrieve and check assumptions about vertex attributes (nodal...
- Getting.Started: Getting Started with "ergm": Fit, simulate and diagnose...
- Getting.Started: Getting Started with "ergm": Fit, simulate and diagnose...
- gof.ergm: Conduct Goodness-of-Fit Diagnostics on a Exponential Family...
- gof.ergm: Conduct Goodness-of-Fit Diagnostics on a Exponential Family...
- is.curved: Testing for curved exponential family
- is.curved: Testing for curved exponential family
- is.durational: Testing for durational dependent models
- is.durational: Testing for durational dependent models
- is.dyad.independent: Testing for dyad-independence
- is.dyad.independent: Testing for dyad-independence
- is.inCH: Determine whether a vector is in the closure of the convex...
- is.inCH: Determine whether a vector is in the closure of the convex...
- kapferer: Kapferer's tailor shop data
- kapferer: Kapferer's tailor shop data
- lasttoggle: Storing last toggle information in a network
- lasttoggle: Storing last toggle information in a network
- logLik.ergm: A 'logLik' method for 'ergm'.
- logLik.ergm: A 'logLik' method for 'ergm'.
- mcmc.diagnostics.ergm: Conduct MCMC diagnostics on an ergm fit
- mcmc.diagnostics.ergm: Conduct MCMC diagnostics on an ergm fit
- mcmc.list_utils: utility operations for mcmc.list objects
- mcmc.list_utils: utility operations for mcmc.list objects
- MHproposal: Functions to initialize the MHproposal object
- MHproposal: Functions to initialize the MHproposal object
- molecule: Synthetic network with 20 nodes and 28 edges
- molecule: Synthetic network with 20 nodes and 28 edges
- network.update: Replaces the sociomatrix in a network object
- network.update: Replaces the sociomatrix in a network object
- newnw.extract: Internal function to create a new network from the ergm MCMC...
- newnw.extract: Internal function to create a new network from the ergm MCMC...
- nvattr.copy.network: Copy network- and vertex-level attributes between two network...
- nvattr.copy.network: Copy network- and vertex-level attributes between two network...
- plot.ergm: Plotting Method for class ergm
- plot.ergm: Plotting Method for class ergm
- plot.gofobject: Plot Goodness-of-Fit Diagnostics on a Exponential Family...
- plot.gofobject: Plot Goodness-of-Fit Diagnostics on a Exponential Family...
- plot.network.ergm: Two-Dimensional Visualization of Networks
- plot.network.ergm: Two-Dimensional Visualization of Networks
- print.ergm: Exponential Random Graph Models
- print.ergm: Exponential Random Graph Models
- samplk: Longitudinal networks of positive affection within a...
- samplk: Longitudinal networks of positive affection within a...
- sampson: Cumulative network of positive affection within a monastery...
- sampson: Cumulative network of positive affection within a monastery...
- san: Use Simulated Annealing to attempt to match a network to a...
- san: Use Simulated Annealing to attempt to match a network to a...
- search.ergmTerms: Search the ergm-terms documentation for appropriate terms
- search.ergmTerms: Search the ergm-terms documentation for appropriate terms
- simulate.ergm: Draw from the distribution of an Exponential Family Random...
- simulate.ergm: Draw from the distribution of an Exponential Family Random...
- standardize.network: Copy a network object enforcing ergm-appropriate guarantees...
- standardize.network: Copy a network object enforcing ergm-appropriate guarantees...
- summary.ergm: Summarizing ERGM Model Fits
- summary.ergm: Summarizing ERGM Model Fits
- summary.gofobject: Summaries the Goodness-of-Fit Diagnostics on a Exponential...
- summary.gofobject: Summaries the Goodness-of-Fit Diagnostics on a Exponential...
- summary.network.list: Summarizing network.list objects
- summary.network.list: Summarizing network.list objects
- summary.statistics: Calculation of network or graph statistics
- summary.statistics: Calculation of network or graph statistics
- vcov.ergm: Extract Model Covariance Matrix
- vcov.ergm: Extract Model Covariance Matrix
- wtd.median: Weighted Median
- wtd.median: Weighted Median