| print.inference | R Documentation | 
Print methods for objects of class
"inference", "termtable", "termeffects",
or "printInference".
## S3 method for class 'inference'
print(x, show = getOption("show.inference"), print=TRUE,
  digits = getOption("digits.reduced"), transpose.ok = TRUE,
  legend = NULL, na.print = getOption("na.print"), ...)
## S3 method for class 'termtable'
print(x, show = getOption("show.inference"), ...)
## S3 method for class 'termeffects'
print(x, show = getOption("show.inference"),
  transpose.ok = TRUE, single = FALSE, print = TRUE, warn = TRUE, ...)
## S3 method for class 'printInference'
print(x, ...)
| x | object to be printed | 
| show | determines items (columns) to be shown | 
| digits | number of significant digits to be printed | 
| transpose.ok | logical: May a single column be shown as a row? | 
| single | logical: Should components with a single coefficient be printed? | 
| legend | logical: should the legend(s) for the symbols
characterizing p-values and relevances be printed?
Defaults to  | 
| na.print | string by which  | 
| print | logical: if  | 
| warn | logical: Should the warning be issued if
 | 
| ... | further arguments, passed to  | 
The value, if assigned to rr, say, can be printed by using
print.printInference, writing print(rr), which is just
what happens internally unless print=FALSE is used.
This allows for editing the result before printing it, see Examples.
printInference objects can be a vector, a data.frame or a
matrix, or a list of such items.
Each item can have an attribute head of mode character that is
printed by cat before the item, and analogous with a
tail attribute. 
A kind of formatted version of x, with class
printInference.
For print.inference, it will be
a character vector or a data.frame with attributes
head and tail if applicable.
For print.termeffects, it will be a list of such elements,
with its own head and tail.
It is invisibly returned.
Werner A. Stahel
twosamples, termtable,
termeffects, inference.
data(d.blast)
r.blast <-
  lm(log10(tremor)~location+log10(distance)+log10(charge), data=d.blast)
rt <- termtable(r.blast)
## print() : first default, then "classical" :
rt
print(rt, show="classical")
class(te <- termeffects(r.blast)) #  "termeffects"
rr <- print(te, print=FALSE)
attr(rr, "head") <- sub("lm", "Linear Regression", attr(rr, "head"))
class(rr) # "printInference"
rr # <==>  print(rr)
str(rr)
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