R help - Jun 2012 - Trying to speed up an if/else statement in simulations

Dear R-help,

I am trying to write a function to simulate datasets of size n which contain
two time-to-event outcome variables with associated
'Event'/'Censored'
indicator variables (flag1 and flag2 respectively). One of these indicator
variables needs to be dependent on the other, so I am creating the first and
trying to use this to create the second using an if/else statement. 

My data structure needs to follow this algorithm (for each row of the data):
If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
otherwise

I can set up this example quite simply using if else statements, but this is
incredibly inefficient when running thousands of datasets:
data<-as.data.frame(rbinom(10,1,0.5))
colnames(data)<-'flag1'
for (i in 1:n) {
  if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
{data$flag2[i]<-rbinom(1,1,0.5)}  
 }


I think to speed up the simulations I would be better changing to
vectorisation and using something like:
ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5)) 
but the rbinom statements here generate one value and repeat this draw for
every element of flag2 that matches the 'if' statement on flag1.

Is there a way to assign flag2 to a new bernoulli draw for each subject in
the data frame with flag1=1?

I hope my question is clear, and thank you in advance for your help. 

Thanks,
Natalie
PhD student, Reading University

P.S. I am using R 2.12.1 on Windows 7.


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inline below

Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org] On Behalf
> Of nqf
> Sent: Monday, June 18, 2012 10:30 AM
> To: r-help at r-project.org
> Subject: [R] Trying to speed up an if/else statement in simulations
> 
> Dear R-help,
> 
> I am trying to write a function to simulate datasets of size n which
contain
> two time-to-event outcome variables with associated
'Event'/'Censored'
> indicator variables (flag1 and flag2 respectively). One of these indicator
> variables needs to be dependent on the other, so I am creating the first
and
> trying to use this to create the second using an if/else statement.
> 
> My data structure needs to follow this algorithm (for each row of the
data):
> If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
> Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
> otherwise
> 
> I can set up this example quite simply using if else statements, but this
is
> incredibly inefficient when running thousands of datasets:
> data<-as.data.frame(rbinom(10,1,0.5))
> colnames(data)<-'flag1'
> for (i in 1:n) {
>   if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
> {data$flag2[i]<-rbinom(1,1,0.5)}
>  }
Do you mean
   n <- 10
   data <- data.frame(flag1 = rbinom(n, 1, 0.5))
   for(i in seq_len(n)) {
      if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
{data$flag2[i]<-rbinom(1,1,0.5)}
  }
?
> 
> 
> I think to speed up the simulations I would be better changing to
> vectorisation and using something like:
> ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5))
> but the rbinom statements here generate one value and repeat this draw for
> every element of flag2 that matches the 'if' statement on flag1.
Assuming that n is nrow(data), use
   data$flag2 <- ifelse(data$flag1==1, rbinom(n, 1, 0.95), rbinom(n, 1, 0.5))
so you get n independent draws from each distribution instead of 1.  I prefer
to factor out the common arguments as in
   data$flag2 <- rbinom(n, 1, ifelse(data$flag1==1, 0.95, 0.5))

   
> 
> Is there a way to assign flag2 to a new bernoulli draw for each subject in
> the data frame with flag1=1?
> 
> I hope my question is clear, and thank you in advance for your help.
> 
> Thanks,
> Natalie
> PhD student, Reading University
> 
> P.S. I am using R 2.12.1 on Windows 7.
> 
> 
> --
> View this message in context:
http://r.789695.n4.nabble.com/Trying-to-speed-up-an-if-
> else-statement-in-simulations-tp4633725.html
> Sent from the R help mailing list archive at Nabble.com.
> 
> ______________________________________________
> R-help at r-project.org mailing list
> 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.

On Jun 18, 2012, at 1:29 PM, nqf wrote:
> Dear R-help,
>
> I am trying to write a function to simulate datasets of size n which  
> contain
> two time-to-event outcome variables with associated
'Event'/'Censored'
> indicator variables (flag1 and flag2 respectively). One of these  
> indicator
> variables needs to be dependent on the other, so I am creating the  
> first and
> trying to use this to create the second using an if/else statement.
>
> My data structure needs to follow this algorithm (for each row of  
> the data):
> If flag1=1 then flag2 should be 1 with probability 0.95 and zero  
> otherwise
> Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
> otherwise
>
> I can set up this example quite simply using if else statements, but  
> this is
> incredibly inefficient when running thousands of datasets:
> data<-as.data.frame(rbinom(10,1,0.5))
> colnames(data)<-'flag1'
> for (i in 1:n) {
>  if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
> {data$flag2[i]<-rbinom(1,1,0.5)}
> }
>
>
> I think to speed up the simulations I would be better changing to
> vectorisation and using something like:
> ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5))
> but the rbinom statements here generate one value and repeat this  
> draw for
> every element of flag2 that matches the 'if' statement on flag1.
>
> Is there a way to assign flag2 to a new bernoulli draw for each  
> subject in
> the data frame with flag1=1?
If the parameters for the the Bernoulli draws stay the same, as they  
appear to do then all you need to do is read the help page for  
`rbinom` and use the appropriate call to create vectors that are as  
long as data$flag.


-- 
David Winsemius, MD
West Hartford, CT

Tena koe Natalie

Does this do what you want?

set.seed(123)
natalie <- matrix(NA, nrow=10^5, ncol=2, dimnames=list(NULL,
paste0('flag', 1:2)))
natalie[,'flag1'] <- rbinom(nrow(natalie), 1, 0.5)
natalie[natalie[,'flag1']==1, 'flag2'] <-
rbinom(sum(natalie[,'flag1']), 1, 0.95)
natalie[natalie[,'flag1']==0, 'flag2'] <-
rbinom(nrow(natalie)-sum(natalie[,'flag1']), 1, 0.5)
tapply(natalie[,'flag2'], natalie[,'flag1'], table)

HTH ....

Peter Alspach

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of nqf
Sent: Tuesday, 19 June 2012 5:30 a.m.
To: r-help at r-project.org
Subject: [R] Trying to speed up an if/else statement in simulations

Dear R-help,

I am trying to write a function to simulate datasets of size n which contain
two time-to-event outcome variables with associated
'Event'/'Censored'
indicator variables (flag1 and flag2 respectively). One of these indicator
variables needs to be dependent on the other, so I am creating the first and
trying to use this to create the second using an if/else statement. 

My data structure needs to follow this algorithm (for each row of the data):
If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
otherwise

I can set up this example quite simply using if else statements, but this is
incredibly inefficient when running thousands of datasets:
data<-as.data.frame(rbinom(10,1,0.5))
colnames(data)<-'flag1'
for (i in 1:n) {
  if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
{data$flag2[i]<-rbinom(1,1,0.5)}  
 }


I think to speed up the simulations I would be better changing to
vectorisation and using something like:
ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5)) 
but the rbinom statements here generate one value and repeat this draw for
every element of flag2 that matches the 'if' statement on flag1.

Is there a way to assign flag2 to a new bernoulli draw for each subject in
the data frame with flag1=1?

I hope my question is clear, and thank you in advance for your help. 

Thanks,
Natalie
PhD student, Reading University

P.S. I am using R 2.12.1 on Windows 7.


--
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http://r.789695.n4.nabble.com/Trying-to-speed-up-an-if-else-statement-in-simulations-tp4633725.html
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I might try something like:

data[data$flag1 == 1, "flag2"] <- runif(sum(data$flag1 == 1)) <
0.95

and similarly for the other case.

Hope this helps,
Michael

On Mon, Jun 18, 2012 at 12:29 PM, nqf <n.j.franklin at pgr.reading.ac.uk>
wrote:
> Dear R-help,
>
> I am trying to write a function to simulate datasets of size n which
contain
> two time-to-event outcome variables with associated
'Event'/'Censored'
> indicator variables (flag1 and flag2 respectively). One of these indicator
> variables needs to be dependent on the other, so I am creating the first
and
> trying to use this to create the second using an if/else statement.
>
> My data structure needs to follow this algorithm (for each row of the
data):
> If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
> Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
> otherwise
>
> I can set up this example quite simply using if else statements, but this
is
> incredibly inefficient when running thousands of datasets:
> data<-as.data.frame(rbinom(10,1,0.5))
> colnames(data)<-'flag1'
> for (i in 1:n) {
> ?if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
> {data$flag2[i]<-rbinom(1,1,0.5)}
> ?}
>
>
> I think to speed up the simulations I would be better changing to
> vectorisation and using something like:
> ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5))
> but the rbinom statements here generate one value and repeat this draw for
> every element of flag2 that matches the 'if' statement on flag1.
>
> Is there a way to assign flag2 to a new bernoulli draw for each subject in
> the data frame with flag1=1?
>
> I hope my question is clear, and thank you in advance for your help.
>
> Thanks,
> Natalie
> PhD student, Reading University
>
> P.S. I am using R 2.12.1 on Windows 7.
>
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/Trying-to-speed-up-an-if-else-statement-in-simulations-tp4633725.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.

Hello,

Try creating an index vector. In this case, I've called it 'one'.
Then, 'n.one' is the number of ones in flag1.

(Since data is an R function, I've renamed your example dat).



n <- 10   # number of observations

# First make up some data
set.seed(123)
dat <- data.frame(flag1=rbinom(n, 1, 0.5))
dat$flag2 <- integer(n)  # creates flag2, all zeros.

one <- dat$flag1 == 1  # logical index vector
n.one <- sum(ix)       # how many
dat$flag2[one]  <- rbinom(n.one, 1, 0.95)    # whenever TRUE, set
dat$flag2[!one] <- rbinom(n - n.one, 1, 0.50) # negation of 'one'
dat


Simple, no? And always faster.

Hope this helps,

Rui Barradas

Em 18-06-2012 18:29, nqf escreveu:
> Dear R-help,
>
> I am trying to write a function to simulate datasets of size n which
contain
> two time-to-event outcome variables with associated
'Event'/'Censored'
> indicator variables (flag1 and flag2 respectively). One of these indicator
> variables needs to be dependent on the other, so I am creating the first
and
> trying to use this to create the second using an if/else statement.
>
> My data structure needs to follow this algorithm (for each row of the
data):
> If flag1=1 then flag2 should be 1 with probability 0.95 and zero otherwise
> Else if flag1=0 then flag2 should be 1 with probability 0.5 and zero
> otherwise
>
> I can set up this example quite simply using if else statements, but this
is
> incredibly inefficient when running thousands of datasets:
> data<-as.data.frame(rbinom(10,1,0.5))
> colnames(data)<-'flag1'
> for (i in 1:n) {
>    if (data$flag1[i]==1) {data$flag2[i]<-rbinom(1,1,0.95)} else
> {data$flag2[i]<-rbinom(1,1,0.5)}
>   }
>
>
> I think to speed up the simulations I would be better changing to
> vectorisation and using something like:
> ifelse(data$flag1==1,rbinom(1,1,0.95),rbinom(1,1,0.5))
> but the rbinom statements here generate one value and repeat this draw for
> every element of flag2 that matches the 'if' statement on flag1.
>
> Is there a way to assign flag2 to a new bernoulli draw for each subject in
> the data frame with flag1=1?
>
> I hope my question is clear, and thank you in advance for your help.
>
> Thanks,
> Natalie
> PhD student, Reading University
>
> P.S. I am using R 2.12.1 on Windows 7.
>
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/Trying-to-speed-up-an-if-else-statement-in-simulations-tp4633725.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> 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.
>

Perfect, I now have a choice of workable solutions. Thanks a lot for your
help, much appreciated.

Natalie

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