print.summary.glmssn: Print summary - S3 Method for Class 'glmssn'

View source: R/summary.glmssn.R

print.summary.glmssnR Documentation

Print summary - S3 Method for Class 'glmssn'

Description

print is a generic function that prints output summaries of fitted models in the SSN package. In particular, the function invokes methods for objects of class summary.glmssn.

Usage

## S3 method for class 'summary.glmssn'
print(x, digits = max(3L, getOption("digits") - 3L),
   signif.stars = getOption("show.signif.stars"), ...)

Arguments

x

an object of class summary.glmssn

digits

the number of significant digits to use when printing.

signif.stars

logical. If 'TRUE', 'significance stars' are printed for each coefficient.

...

other arguments passed to print

Details

The print.summary.glmssn function summarizes and prints the fitted model with a table of estimates for the fixed effects and the covariance parameter estimates.

Value

Prints the summary beginning with call and arguments used, plus:

Residuals

a summary of the min, max, and quartiles of the usual residuals.

Coefficients

a p x 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value. Aliased coefficients are omitted.

Covariance Parameters

a list of covariance parameter estimates for each covariance model.

Residual standard error

the square-root of the sum of all of the variance (partial sill) parameters.

Generalized R-squared

the generalized R-squared value of the fitted model

Author(s)

Jay Ver Hoef support@SpatialStreamNetworks.com

See Also

glmssn,link{covparms}

Examples


	library(SSN)
	data(modelFits)
	#for examples only, make sure fitSp has the correct path
	#if you use importSSN(), path will be correct
	fitSp$ssn.object <- updatePath(fitSp$ssn.object, 
		paste0(tempdir(),'/MiddleFork04.ssn'))
	names(fitSp)
	names(fitSp$ssn.object)

  print(summary(fitSp))
  #the same effect is achieved with this
  summary(fitSp)
  #or this
  fitSp

SSN documentation built on March 7, 2023, 5:30 p.m.