Your desire is not unusual among novices... but it is really not a good idea 
for your function to be making those decisions. Look at how R does things:

The lm function prints nothing... it returns an object containing the result of 
a linear regression. If you happen to call it directly from the R command 
prompt and don't assign it to a variable, then the command interpreter notices 
that return value and prints it. Since the lm object has a dedicated print 
method associated with it, that output looks different than a plain list object 
would... but the fact that it has a special print method (?print.lm) is just 
window dressing unrelated to your request.

The important part is that the lm function doesn't even consider printing 
anything out... it is the code that calls the function that determines whether 
it will get printed. So...

lm( hp ~ disp, data = mtcars )  # printed by command interpreter
z <- lm( hp ~ disp, data = mtcars ) # assignment operator returns the value of 
z to the command processor, but invisibly
( z <- lm( hp ~ disp, data = mtcars ) ) # strips off the invisible marking so 
the value gets printed

Another example:

f <- function() {
  x <- 4
  x  # doesn't print
  invisible( 5 ) # return invisible result
}

f()  # doesn't print 4 because there is no command prompt looking at x alone on 
a line... it is inside f
# command prompt doesn't print 5 because that 5 has been marked as invisible
(f()) # command interpreter prints 5

Leaving it up to the calling code to decide whether to print gives you the 
option of calling your analysis function possibly thousands of times and 
figuring out some slick way to summarize all those runs without thousands of 
printouts that you are not going to wade through anyway and would only slow the 
computer down (printing really does slow the computer down!)


On March 25, 2024 9:00:49 PM PDT, Steven Yen <st...@ntu.edu.tw> wrote:
>I just like the subroutine to spit out results (Mean, Std.dev, etc.) and also 
>be able to access the results for further processing, i.e.,
>
>v$Mean
>
>v$Std.dev
>
>On 3/26/2024 11:24 AM, Richard O'Keefe wrote:
>> Not clear what you mean by "saved".
>> If you call a function and the result is printed, the result is
>> remembered for a wee while in
>> the variable .Last.value, so you can do
>>> function.with.interesting.result(.......)
>>> retained.interesting.result <- .Last.value
>> or even
>>> .Last.value -> retained.interesting.result
>> If you know before you start writing the expression that you want to
>> save the value,
>> you can wrap the assignment in parentheses, making it an expression:
>> 
>>> (retained.interesting.result <- function.with.interesting.result(......))
>> 
>> On Tue, 26 Mar 2024 at 15:03, Steven Yen <st...@ntu.edu.tw> wrote:
>>> How can I have both printout and saved results at the same time.
>>> 
>>> The subroutine first return "out" and the printout gets printed, but not
>>> saved.
>>> 
>>> I then run the "invisible" line. Results got saved and accessible but no
>>> printout.
>>> 
>>> How can I have both printout and also have the results saved? Thank you!
>>> 
>>>   > dstat4 <- function(data,digits=3){
>>> +   Mean    <- apply(data,2,mean,na.rm=TRUE)
>>> +   Std.dev <- apply(data,2,sd,  na.rm=TRUE)
>>> +   Min <- apply(data,2,min,na.rm=TRUE)
>>> +   Max <- apply(data,2,max,na.rm=TRUE)
>>> +   Obs <- dim(data)[1]
>>> +   out <-round(cbind(Mean,Std.dev,Min,Max,Obs),digits)
>>> +   out
>>> + # invisible(list(Mean=Mean,Std.dev=Std.dev,Min=Min,Max=Max))
>>> + }
>>>   > x1<-rnorm(n=5,mean=5, sd=1)
>>>   > x2<-rnorm(n=5,mean=10,sd=2)
>>>   > w<-rnorm(n=5,mean=2,sd=0.3)
>>>   > mydata<-data.frame(cbind(x1,x2))
>>>   > v<-dstat4(mydata); v
>>>        Mean Std.dev   Min    Max Obs
>>> x1  5.000   0.922 3.900  6.282   5
>>> x2 10.769   1.713 9.209 13.346   5
>>>   > v$Mean
>>> Error in v$Mean : $ operator is invalid for atomic vectors
>>>   > dstat4 <- function(data,digits=3){
>>> +   Mean    <- apply(data,2,mean,na.rm=TRUE)
>>> +   Std.dev <- apply(data,2,sd,  na.rm=TRUE)
>>> +   Min <- apply(data,2,min,na.rm=TRUE)
>>> +   Max <- apply(data,2,max,na.rm=TRUE)
>>> +   Obs <- dim(data)[1]
>>> +   out <-round(cbind(Mean,Std.dev,Min,Max,Obs),digits)
>>> + # out
>>> +   invisible(list(Mean=Mean,Std.dev=Std.dev,Min=Min,Max=Max))
>>> + }
>>> 
>>>   > v<-dstat4(mydata)
>>>   > v$Mean
>>>         x1       x2
>>> 4.233051 9.564454
>>> 
>>> ______________________________________________
>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>
>______________________________________________
>R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.

-- 
Sent from my phone. Please excuse my brevity.

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