Skip to contents

Compact one-screen description of nethist, multinethist, and hnethist objects. The estimated probabilities are reported by their dimensions only; use summary.network_histogram for the model fit statistics and object$thetahat for the values themselves.

Usage

# S3 method for class 'nethist'
print(x, digits = getOption("digits"), ...)

# S3 method for class 'multinethist'
print(x, digits = getOption("digits"), ...)

# S3 method for class 'hnethist'
print(x, digits = getOption("digits"), ...)

Arguments

x

a nethist, multinethist, or hnethist object.

digits

number of significant digits used when printing the loss.

...

additional arguments. Currently unused.

Value

The input object, invisibly.

Examples

# \donttest{
set.seed(42)
data(polblog)
fit <- suppressMessages(nethist(polblog))
print(fit)
#> 
#> Network histogram fit (nethist)
#> 
#> Nodes: 1224   Blocks: 16   Bandwidth: 73
#> Method: Profile Likelihood
#> thetahat: 16 x 16 probability matrix
#> Normalized log-likelihood: -2.969964
#> 
#> Use summary() for details.
summary(fit)
#> 
#> Network histogram fit (nethist)
#> 
#> Nodes: 1224   Blocks: 16   Bandwidth: 73
#> Method: Profile Likelihood
#> Edge density (rho_hat): 0.02233205
#> 
#> Model fit:
#>   Normalized log-likelihood: -2.969964
#>   Log-likelihood: -49642.94  (df = 136)
#>   AIC: 99557.89   BIC: 101125.4
#>   Mean squared error: 0.01769046
#> 
#> thetahat: 16 x 16 probability matrix (use fitted() or $thetahat)
# }