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Re: st: Drawing from a known, non-regular, discrete distribution
From
Nick Cox <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: Drawing from a known, non-regular, discrete distribution
Date
Tue, 18 Feb 2014 12:37:40 +0000
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
[email protected]
On 18 February 2014 09:35, Nick Cox <[email protected]> wrote:
> The "mapping" (if I am guessing correctly) is in fact trivial as in
> effect your sample would just be the observation numbers.
> Nick
> [email protected]
>
>
> On 18 February 2014 09:32, Nick Cox <[email protected]> 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
>> [email protected]
>>
>>
>> On 18 February 2014 09:17, Lulu Zeng <[email protected]> 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 <[email protected]> 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
>>>> [email protected]
>>>>
>>>>
>>>> On 18 February 2014 03:58, Lulu Zeng <[email protected]> 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
>>>>> <[email protected]> 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 <[email protected]> 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/