print.ols

digits

set to <code>TRUE</code> to print the correlation matrix of
  parameter estimates

long

specify <code>coefs=FALSE</code> to suppress printing the table
  of model coefficients, standard errors, etc.  Specify <code>coefs=n</code>
  to print only the first <code>n</code> regression coefficients in the
  model.

coefs

a logical value indicating whether information should be
  formatted as plain text or as LaTeX markup

latex

a character string title to be passed to <code>prModFit</code>

title

other parameters to pass to <code>print</code> or <code>format</code>

formatted printing of an object of class <code>ols</code> using methods taken from
<code>print.lm</code> and <code>summary.lm</code>. Prints R-squared, adjusted R-squared,
parameter estimates,
standard errors, and t-statistics (Z statistics if penalized estimation was used).
For penalized
estimation, prints the maximum penalized likelihood estimate of the residual
standard deviation (<code>Sigma</code>) instead of the usual root mean squared error.

print

Regression modeling, testing, estimation, validation,
	graphics, prediction, and typesetting by storing enhanced model design
	attributes in the fit.  rms is a collection of functions that
	assist with and streamline modeling.  It also contains functions for
	binary and ordinal logistic regression models, ordinal models for
  continuous Y with a variety of distribution families, and the Buckley-James
	multiple regression model for right-censored responses, and implements
	penalized maximum likelihood estimation for logistic and ordinary
	linear models.  rms works with almost any regression model, but it
	was especially written to work with binary or ordinal regression
	models, Cox regression, accelerated failure time models,
	ordinary linear models,	the Buckley-James model, generalized least
	squares for serially or spatially correlated observations, generalized
	linear models, and quantile regression.

print.ols: Print ols

Description

Usage

Arguments

See Also