qqplot for binomial distribution

Dear All,

when I do :

set.seed(123)

expected_distribution<-rbinom(1000,100,.05)

#Without jitter

qqplot(jitter(expected_distribution),count1_vector, xlab="Expected
distribution",ylab="Observed values")
qqline(count1_vector,distribution = function(probs) { qbinom(probs,
size=100, prob=0.05) },col = "red",lwd = 2)

I get a line through the middle. Is this satisfactory ?

#With jitter
qqplot(jitter(expected_distribution),jitter(count1_vector),xlab="Expected
distribution",ylab="Observed values")
qqline(jitter(count1_vector),distribution = function(probs) { qbinom(probs,
size=100, prob=0.05) },col = "red",lwd = 2)

Now I can see the line is  not exactly through the middle. Can I think that
this is due to the way the data is discretized?

count1_vector <-
c(2, 6, 5, 8, 8, 6, 8, 3, 5, 8, 7, 6, 4, 7, 5, 2, 3, 3, 6, 3,
7, 3, 4, 8, 6, 6, 3, 5, 5, 3, 4, 5, 4, 2, 3, 6, 7, 7, 5, 4, 4,
7, 9, 4, 4, 4, 8, 9, 3, 5, 4, 7, 4, 3, 8, 6, 5, 5, 7, 3, 6, 7,
8, 7, 9, 3, 5, 5, 9, 8, 7, 7, 2, 3, 5, 2, 4, 14, 7, 7, 7, 3,
5, 4, 2, 12, 3, 6, 9, 4, 4, 3, 4, 4, 4, 6, 7, 4, 6, 10, 8, 5,
3, 3, 1, 3, 4, 3, 7, 3, 9, 7, 3, 3, 7, 5, 1, 2, 2, 3, 5, 4, 3,
8, 7, 0, 5, 3, 3, 4, 9, 2, 7, 5, 5, 5, 7, 7, 5, 4, 7, 2, 3, 5,
4, 5, 2, 10, 6, 3, 6, 2, 11, 2, 5, 5, 2, 5, 2, 10, 4, 5, 9, 1,
5, 6, 3, 4, 7, 7, 2, 2, 3, 6, 6, 6, 7, 3, 3, 6, 1, 4, 4, 4, 10,
4, 7, 4, 3, 4, 6, 5, 6, 7, 3, 7, 3, 5, 6, 6, 4, 5, 1, 7, 5, 7,
6, 7, 5, 3, 6, 7, 10, 5, 5, 4, 9, 6, 3, 9, 8, 4, 2, 8, 10, 4,
6, 7, 4, 4, 8, 4, 5, 4, 5, 6, 6, 5, 8, 2, 2, 6, 5, 3, 7, 7, 4,
9, 6, 5, 7, 8, 6, 1, 2, 3, 4, 4, 6, 8, 5, 8, 5, 7, 7, 4, 6, 3,
4, 5, 3, 4, 5, 3, 3, 4, 5, 5, 7, 8, 6, 5, 3, 3, 4, 3, 8, 6, 6,
3, 0, 4, 2, 7, 3, 5, 4, 6, 7, 4, 7, 6, 5, 8, 6, 7, 4, 5, 3, 6,
7, 6, 3, 5, 3, 3, 6, 3, 3, 2, 7, 5, 10, 2, 4, 5, 2, 4, 10, 5,
2, 7, 8, 5, 3, 7, 4, 2, 4, 3, 5, 6, 8, 10, 3, 7, 5, 8, 5, 2,
6, 8, 6, 7, 8, 2, 4, 2, 4, 3, 2, 4, 4, 2, 4, 3, 12, 2, 11, 5,
8, 8, 3, 6, 2, 6, 3, 5, 4, 8, 4, 5, 7, 2, 5, 3, 5, 3, 7, 6, 5,
2, 8, 6, 3, 3, 5, 3, 2, 6, 5, 8, 7, 4, 2, 3, 5, 2, 6, 4, 9, 5,
4, 4, 2, 1, 3, 3, 2, 5, 7, 6, 4, 4, 5, 6, 7, 4, 4, 4, 5, 9, 7,
5, 3, 5, 5, 2, 11, 9, 6, 8, 6, 6, 8, 6, 3, 6, 3, 7, 3, 3, 7,
4, 7, 4, 8, 3, 4, 8, 8, 8, 7, 4, 6, 1, 3, 7, 5, 13, 8, 1, 8,
5, 1, 3, 5, 4, 6, 5, 4, 3, 3, 7, 5, 5, 5, 3, 5, 5, 1, 8, 6, 4,
5, 9, 3, 8, 6, 4, 7, 6, 7, 5, 5, 6, 2, 7, 8, 11, 10, 4, 8, 5,
5, 4, 5, 4, 2, 8, 3, 3, 4, 5, 7, 12, 4, 7, 5, 4, 9, 8, 4, 5,
9, 4, 6, 5, 5, 2, 3, 4, 7, 7, 7, 7, 1, 6, 6, 6, 4, 8, 8, 5, 7,
3, 4, 6, 2, 6, 6, 4, 8, 4, 3, 7, 1, 4, 6, 2, 3, 5, 5, 9, 7, 1,
4, 1, 5, 3, 5, 4, 3, 5, 10, 4, 8, 6, 4, 3, 5, 6, 4, 6, 6, 4,
7, 7, 6, 5, 4, 4, 6, 10, 6, 5, 3, 8, 3, 4, 3, 5, 5, 2, 6, 6,
8, 2, 5, 9, 6, 5, 5, 4, 10, 7, 3, 5, 6, 8, 5, 3, 3, 7, 3, 4,
6, 2, 9, 2, 6, 5, 3, 6, 2, 4, 3, 4, 5, 5, 1, 5, 4, 11, 4, 1,
9, 5, 4, 7, 2, 11, 4, 9, 6, 5, 5, 6, 6, 7, 9, 4, 4, 4, 4, 3,
7, 3, 3, 4, 2, 6, 6, 6, 4, 6, 2, 5, 6, 5, 4, 3, 4, 7, 8, 7, 3,
5, 4, 4, 4, 4, 4, 4, 2, 7, 3, 5, 7, 1, 5, 5, 2, 7, 3, 3, 5, 3,
5, 4, 9, 5, 7, 8, 7, 7, 4, 5, 3, 5, 6, 5, 1, 6, 5, 5, 8, 7, 3,
6, 8, 1, 12, 1, 7, 6, 6, 3, 4, 4, 2, 2, 3, 2, 8, 4, 3, 7, 9,
10, 5, 5, 6, 7, 3, 7, 4, 7, 7, 3, 5, 9, 7, 3, 6, 6, 2, 5, 4,
3, 5, 8, 5, 6, 3, 4, 5, 2, 4, 3, 4, 5, 2, 7, 2, 7, 5, 5, 6, 8,
4, 8, 6, 5, 4, 5, 1, 6, 6, 2, 4, 8, 5, 7, 6, 10, 6, 4, 4, 4,
9, 5, 3, 1, 10, 7, 5, 6, 4, 7, 5, 6, 4, 2, 4, 6, 5, 3, 3, 6,
5, 9, 3, 7, 9, 4, 1, 4, 2, 4, 5, 4, 4, 2, 7, 11, 3, 3, 5, 8,
3, 5, 7, 9, 6, 11, 6, 5, 3, 7, 5, 3, 7, 4, 5, 4, 4, 8, 3, 3,
5, 4, 3, 7, 4, 2, 10, 2, 4, 3, 8, 4, 4, 5, 3, 3, 6, 2, 7, 2,
2, 11, 1, 6, 3, 6, 5, 7, 3, 3, 1, 7, 9, 8, 7, 2, 5, 4, 3, 7,
7, 2, 5, 4, 3, 3, 6, 10, 4, 9, 6, 5, 3, 4, 5, 5, 6, 6, 7, 3,
4, 8, 6, 4, 5, 1, 5, 9, 3, 6, 2, 4, 5, 5, 3, 3, 3, 3, 5, 4, 4,
5, 5, 1, 4, 5, 8, 7, 4, 3, 3, 5, 5, 4, 6, 5, 4, 7, 4, 4, 3, 3,
8, 4, 6, 7, 3, 4, 3, 5, 5, 7, 3, 6, 9, 7, 4, 3, 2, 6)








On Wed, Apr 19, 2017 at 12:32 PM, Ashim Kapoor <ashimkapoor at gmail.com>
wrote:

Dear Boris,

Many thanks,
Ashim

On Tue, Apr 18, 2017 at 7:56 PM, Boris Steipe <boris.steipe at utoronto.ca>
wrote:

As per the help pages, the data samples are expected in the second
argument, "y".

So try
  qqplot(rbinom(n=100, size=100, p=0.05), count1_vector)

... and then plot your qqline()

Alternatively, try

qqline(count1_vector,
       distribution = function(probs) { qbinom(probs, size=100,
prob=0.05) },
       datax = TRUE, # <- logical. Should data values be on the x-axis?
       col = "red",
       lwd = 0.5)
... and use your original qqplot()


B.

On Apr 18, 2017, at 12:47 AM, Ashim Kapoor <ashimkapoor at gmail.com>

wrote:

Dear Boris,

Thank you for your reply.

dput(count1_vector)

c(5, 6, 4, 4, 6, 5, 4, 5, 3, 7, 5, 5, 3, 4, 8, 6, 10, 2, 4, 6,
8, 4, 4, 6, 8, 5, 6, 3, 7, 9, 4, 7, 5, 7, 3, 4, 5, 2, 11, 7,
8, 5, 5, 6, 3, 2, 3, 5, 9, 6, 5, 6, 7, 3, 10, 7, 6, 4, 9, 5,
7, 3, 7, 3, 2, 3, 4, 5, 10, 4, 5, 5, 6, 7, 4, 8, 7, 5, 5, 4,
8, 7, 9, 4, 4, 4, 7, 5, 4, 10, 4, 5, 6, 1, 3, 5, 4, 7, 4, 6)

set.seed(123)
qqplot(count1_vector,rbinom(n=100,size=100,p=.05))
qqline(count1_vector,distribution = function(probs) { qbinom(probs,

size=100, prob=0.05) },

       col = "red",
       lwd = 0.5)

When I do this, the line does not pass through the center of my data.I

do expect count1_vector to be 100 samples of binomial with n=100 and p=.05.

Any comments or suggestions for me ?

Note : I built a 95% Confidence interval for my data and I counted how

often out of 100 times did the data fall outside the CI.This I expect to be
binomial with n=100,p=.05. I repeated this a 100 times and obtained
count1_vector.

Best Regards,
Ashim.


On Mon, Apr 17, 2017 at 7:51 PM, Boris Steipe <boris.steipe at utoronto.ca>

wrote:

That's not how qqline() works. The line is drawn with respect to a

_reference_distribution_ which is the normal distribution by default. For
the binomial distribution, you need to specify the distribution argument.
There is an example in the help page that shows you how this is done for
qchisq(). for qbinom() it is:

set.seed(123)
qqplot(rbinom(n=100, size=100, p=0.05),
       rbinom(n=100, size=100, p=0.05) )

qqline(rbinom(n=100,size=100,p=.05),
       distribution = function(probs) { qbinom(probs, size=100,

prob=0.05) },

       col = "red",
       lwd = 0.5)




B.

On Apr 17, 2017, at 9:15 AM, Ashim Kapoor <ashimkapoor at gmail.com>

wrote:

Dear Spencer,

Okay. Many thanks. My next query is how do I use qqline?

When I try

qqline(rbinom(n=100,size=100,p=.05))

I don't get the line in the right place.

Best Regards,
Ashim

On Mon, Apr 17, 2017 at 6:31 PM, Spencer Graves <
spencer.graves at effectivedefense.org> wrote:

On 2017-04-17 7:58 AM, Ashim Kapoor wrote:

Dear All,

set.seed(123)
qqplot(rbinom(n=100,size=100,p=.05), rbinom(n=100,size=100,p=.05) )

I expect to see 1 clear line,but I don't. What am I

misunderstanding?

     The distribution is discrete, and points are superimposed. Try

the

following:


set.seed(123)
qqplot(jitter(rbinom(n=100,size=100,p=.05)),
      jitter(rbinom(n=100,size=100,p=.05) ))


     Spencer Graves

Best Regards,
Ashim

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PLEASE do read the posting guide http://www.R-project.org/posti
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and provide commented, minimal, self-contained, reproducible code.

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______________________________________________
R-help at 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/posti

ng-guide.html

and provide commented, minimal, self-contained, reproducible code.