print.pcsslm: Print an object of class pcsslm

In jackmwolf/pcsstools: Tools for Regression Using Pre-Computed Summary Statistics

Print an object of class pcsslm

Description

Prints a linear model fit through pre-computed summary statistics

Usage

## S3 method for class 'pcsslm'
print(
  x,
  digits = max(3L, getOption("digits") - 3L),
  symbolic.cor = x$symbolic.cor,
  signif.stars = getOption("show.signif.stars"),
  ...
)

Arguments

x	an object of class "pcsslm"
digits	the number of significant digits to use when printing.
symbolic.cor	logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.
signif.stars	logical. If TRUE, 'significance stars' are printed for each coefficient.
...	further arguments passed to or from other methods.

Value

an object of class "pcsslm".

An object of class "pcsslm" is a list containing at least the following components:

call	the matched call
terms	the terms object used
coefficients	a p x 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value.
sigma	the square root of the estimated variance of the random error.
df	degrees of freedom, a 3-vector p, n-p, p*, the first being the number of non-aliased coefficients, the last being the total number of coefficients.
fstatistic	a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
r.squared	R^2, the 'fraction of variance explained by the model'.
adj.r.squared	the above R^2 statistic 'adjusted', penalizing for higher p.
cov.unscaled	a p x p matrix of (unscaled) covariances of the coef[j], j=1,...p.
Sum Sq	a 3-vector with the model's Sum of Squares Regression (SSR), Sum of Squares Error (SSE), and Sum of Squares Total (SST).

Author(s)

R Core Team and contributors worldwide. Modified by Jack Wolf

jackmwolf/pcsstools documentation built on July 7, 2024, 7:46 p.m.