Notice: On April 23, 2014, Statalist moved from an email list to a forum, based at statalist.org.
| From | Lulu Zeng <luluzengnz@gmail.com> |
| To | "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |
| Subject | Re: st: Drawing from a known, non-regular, discrete distribution |
| Date | Wed, 19 Feb 2014 20:20:20 +1100 |
Dear Nick and others,
I have 1200 observations in my dataset.
1200 observations (of variable "share") define the probabilities (add
up to 1) & 1200 pre-defined corresponding values to be drawn from
(saved in variable "odo").
I am thinking of having 1000 draws in my sample.
My data looks like below (but with more points). Draw value is
pre-defined, each of them has a probability attached.
Draw value Probability
0.5 0.15
0.6 0.30
0.2 0.25
0.9 0.30
Thank you for your consideration :)
Best Regards,
Lulu
On Wed, Feb 19, 2014 at 7:59 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> My own thoughts on "Thanks in advance" are codified in the FAQ.
> Seemingly no-one agrees with me.
>
> I will pose some questions here, but given other commitments I won't
> be able to respond to any answers until _much_ later today, local
> time. If someone else picks this up before then, fine by me,
> naturally!
>
> How many observations are in your dataset?
> How many observations define the probabilities?
> How many values do you want in your sample?
>
> Nick
> njcoxstata@gmail.com
>
>
>
> On 19 February 2014 08:51, Lulu Zeng <luluzengnz@gmail.com> wrote:
>> Dear Nick,
>>
>> Sorry that the (1..10)' in my example was a typo, I in fact used 1200
>> instead of 10 in my real experiment. It didn't work despite so. I also
>> scaled "share" before calling meta, same error occurs.
>>
>> Also, by using -rdiscrete()-, I can see it draws a random number
>> according to a distribution specified by "p" (and write the random
>> draws into "odo2" using -st_store()- in my case), but I don't
>> understand how -rdiscrete()- could draw from a given set of values
>> (e.g., a pre-specified "odo2" -- this is really what I'm trying to do)
>> instead of random values.
>>
>> My apologies if the answer to my question is straight forward, I am
>> quite new to Meta.
>>
>> Thank you very much for your help in advance Nick.
>>
>> Best Regards,
>> Lulu
>>
>>
>>
>> On Wed, Feb 19, 2014 at 11:54 AM, Nick Cox <njcoxstata@gmail.com> wrote:
>>> In my example, I have 10 probabilities in observations 1 to 10 of the
>>> data, so use
>>> (1..10)' as an argument. That will make sense for you if and only if
>>> your probabilities are the same. See also help for -st_data()-.
>>> Nick
>>> njcoxstata@gmail.com
>>>
>>>
>>> On 19 February 2014 00:09, Lulu Zeng <luluzengnz@gmail.com> wrote:
>>>> Dear Nick,
>>>>
>>>> Thank you for your suggestion. I must have done something incorrectly
>>>> so mata still gives me the below error despite I did use -p :/ sum(p)-
>>>> for rescaling as you suggested (I also tried to rescale the original
>>>> probability variable but neither worked):
>>>>
>>>> sum of the probabilities must be 1
>>>> rdiscrete(): 3300 argument out of range
>>>> <istmt>: - function returned error
>>>> r(3300);
>>>>
>>>>
>>>> My probability variable is "share", and "odo2" is my equivalent of
>>>> your "y". All I did was:
>>>>
>>>> mata
>>>>
>>>> p = st_data((1..10)', "share")
>>>>
>>>> p :/ sum(p)
>>>>
>>>> st_store(., "odo2", rdiscrete(st_nobs(), 1, p)) [this is where
>>>> the error occurs]
>>>>
>>>>
>>>> My apologies for coming back with the same question again.
>>>>
>>>>
>>>> Best Regards,
>>>> Lulu
>>>>
>>>> On Tue, Feb 18, 2014 at 11:37 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>>>> Here is an example of using -rdiscrete()- in Mata. In your case, the
>>>>> probabilities are already in a variable. If -rdiscrete()- chokes on
>>>>> small differences in total from 1, then check the probabilities and if
>>>>> need be scale by -p :/ sum(p)-.
>>>>>
>>>>> . clear
>>>>>
>>>>> . set obs 1000
>>>>> obs was 0, now 1000
>>>>>
>>>>> . mat p = [0.2,0.2,0.1,0.1,0.1,0.1,0.05,0.05,0.05,0.05]
>>>>>
>>>>> . gen double p = p[1,_n]
>>>>> (990 missing values generated)
>>>>>
>>>>> . list in 1/10, sep(0)
>>>>>
>>>>> +-----+
>>>>> | p |
>>>>> |-----|
>>>>> 1. | .2 |
>>>>> 2. | .2 |
>>>>> 3. | .1 |
>>>>> 4. | .1 |
>>>>> 5. | .1 |
>>>>> 6. | .1 |
>>>>> 7. | .05 |
>>>>> 8. | .05 |
>>>>> 9. | .05 |
>>>>> 10. | .05 |
>>>>> +-----+
>>>>>
>>>>> . gen y = .
>>>>> (1000 missing values generated)
>>>>>
>>>>> . mata
>>>>> ------------------------------------------------- mata (type end to
>>>>> exit) ------------------
>>>>> : p = st_data((1..10)', "p")
>>>>>
>>>>> : st_store(., "y", rdiscrete(st_nobs(), 1, p))
>>>>>
>>>>> : end
>>>>> --------------------------------------------------------------------------------------------
>>>>>
>>>>> . tab y
>>>>>
>>>>> y | Freq. Percent Cum.
>>>>> ------------+-----------------------------------
>>>>> 1 | 202 20.20 20.20
>>>>> 2 | 200 20.00 40.20
>>>>> 3 | 98 9.80 50.00
>>>>> 4 | 102 10.20 60.20
>>>>> 5 | 87 8.70 68.90
>>>>> 6 | 99 9.90 78.80
>>>>> 7 | 49 4.90 83.70
>>>>> 8 | 54 5.40 89.10
>>>>> 9 | 53 5.30 94.40
>>>>> 10 | 56 5.60 100.00
>>>>> ------------+-----------------------------------
>>>>> Total | 1,000 100.00
>>>>> Nick
>>>>> njcoxstata@gmail.com
>>>>>
>>>>>
>>>>> On 18 February 2014 09:35, Nick Cox <njcoxstata@gmail.com> wrote:
>>>>>> The "mapping" (if I am guessing correctly) is in fact trivial as in
>>>>>> effect your sample would just be the observation numbers.
>>>>>> Nick
>>>>>> njcoxstata@gmail.com
>>>>>>
>>>>>>
>>>>>> On 18 February 2014 09:32, Nick Cox <njcoxstata@gmail.com> wrote:
>>>>>>> Thanks for the details.
>>>>>>>
>>>>>>> The Mata function -rdiscrete()- should do most of whar you want. You
>>>>>>> will need to map your values to integers 1 up and then read in the
>>>>>>> probabilities so that they are copied from a variable to a vector in
>>>>>>> Mata. Then select integers and reverse the mapping.
>>>>>>>
>>>>>>> Nick
>>>>>>> njcoxstata@gmail.com
>>>>>>>
>>>>>>>
>>>>>>> On 18 February 2014 09:17, Lulu Zeng <luluzengnz@gmail.com> wrote:
>>>>>>>> Dear Nick,
>>>>>>>>
>>>>>>>> My apologies for the unclear description.
>>>>>>>>
>>>>>>>> 1. I have 2 variables in Stata, one variable holds the 1200 known,
>>>>>>>> discrete values I want to draw; the other holds the corresponding
>>>>>>>> probabilities.
>>>>>>>>
>>>>>>>> 2. The 2 variables are associated with a parameter (attribute) of a
>>>>>>>> random utility model. I am trying to draw from the distribution of
>>>>>>>> this parameter of interest, and then divide it by the price parameter
>>>>>>>> (which similarly has 2 associated variables too) to obtain a
>>>>>>>> distribution of willingness to pay.
>>>>>>>>
>>>>>>>>
>>>>>>>> Best Regards,
>>>>>>>> Lulu
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>>
>>>>>>>> On Tue, Feb 18, 2014 at 7:47 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>>>>>>>> You have not, so far as I can see, specified
>>>>>>>>>
>>>>>>>>> 1. How you are holding information on your distribution. Is it 1200
>>>>>>>>> known values with associated probabilities (so as two variables in
>>>>>>>>> Stata), or is the information still outside Stata in some form?
>>>>>>>>>
>>>>>>>>> 2. What you expect to draw as a sample.
>>>>>>>>> Nick
>>>>>>>>> njcoxstata@gmail.com
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> On 18 February 2014 03:58, Lulu Zeng <luluzengnz@gmail.com> wrote:
>>>>>>>>>> Dear Scott,
>>>>>>>>>>
>>>>>>>>>> Thank you for your response. My apologies that I am still a little
>>>>>>>>>> confused about how to do this in my case where I have 1,200
>>>>>>>>>> observation. Can I still use the cond() command without typing in each
>>>>>>>>>> point of the draw?
>>>>>>>>>>
>>>>>>>>>> Best Regards,
>>>>>>>>>> Lulu
>>>>>>>>>>
>>>>>>>>>> On Tue, Feb 18, 2014 at 1:50 PM, Scott Merryman
>>>>>>>>>> <scott.merryman@gmail.com> wrote:
>>>>>>>>>>> http://www.stata.com/statalist/archive/2012-08/msg00256.html
>>>>>>>>>>>
>>>>>>>>>>> and the links within.
>>>>>>>>>>>
>>>>>>>>>>> Scott
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> On Sun, Feb 16, 2014 at 9:15 PM, Lulu Zeng <luluzengnz@gmail.com> wrote:
>>>>>>>>>>>> Dear Statalist,
>>>>>>>>>>>>
>>>>>>>>>>>> I am seeking help with taking draws from a known, non-regular (not
>>>>>>>>>>>> normal or lognormal etc), discrete distribution.
>>>>>>>>>>>>
>>>>>>>>>>>> For example, taking draws from a distribution like the one below.
>>>>>>>>>>>> However, in my case I have 1,200 points instead of the 4 points given
>>>>>>>>>>>> in the example.
>>>>>>>>>>>>
>>>>>>>>>>>> Draw value Probability
>>>>>>>>>>>>
>>>>>>>>>>>> 0.5 0.15
>>>>>>>>>>>>
>>>>>>>>>>>> 0.6 0.30
>>>>>>>>>>>>
>>>>>>>>>>>> 0.2 0.25
>>>>>>>>>>>>
>>>>>>>>>>>> 0.9 0.30
>>>>>>>>>>>>
>>>>>>>>>>>> The "draw value" is the value to be drawn, "probability" is the chance
>>>>>>>>>>>> each value be drawn, so it adds up to 1.
>>>>>>>>>>> *
>>>>>>>>>>> * For searches and help try:
>>>>>>>>>>> * http://www.stata.com/help.cgi?search
>>>>>>>>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>>>>>>>>> * http://www.ats.ucla.edu/stat/stata/
>>>>>>>>>> *
>>>>>>>>>> * For searches and help try:
>>>>>>>>>> * http://www.stata.com/help.cgi?search
>>>>>>>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>>>>>>>> * http://www.ats.ucla.edu/stat/stata/
>>>>>>>>> *
>>>>>>>>> * For searches and help try:
>>>>>>>>> * http://www.stata.com/help.cgi?search
>>>>>>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>>>>>>> * http://www.ats.ucla.edu/stat/stata/
>>>>>>>> *
>>>>>>>> * For searches and help try:
>>>>>>>> * http://www.stata.com/help.cgi?search
>>>>>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>>>>>> * http://www.ats.ucla.edu/stat/stata/
>>>>> *
>>>>> * For searches and help try:
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>>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>>> * http://www.ats.ucla.edu/stat/stata/
>>>> *
>>>> * For searches and help try:
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>>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>>> * http://www.ats.ucla.edu/stat/stata/
>>> *
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>> *
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> *
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