> On Nov 19, 2015, at 7:35 AM, C W <tmrs...@gmail.com> wrote:
>
> ah. Let me fix that and get back to you.
>
> On a side note, why can't I put fn inside curve(), why do I have to use
> Vectorize()?
>
> Here's the code and the message:
>>>>> fn <- function(theta){
>>>>>
>>>>> sum(0.5 * (xvec - rep(theta, 7)) ^ 2 / 1 + 0.5 * log(1))
>>>>>
>>>>> }
>
>> curve(fn, -5, 20)
> Error in curve(fn, -5, 20) :
> 'expr' did not evaluate to an object of length ’n’
The sum function is not vectorized. In oder for a function to be considered
“vectorized”, it needs to return a vector of the same length as its input.
—
David.
>
>
> On Thu, Nov 19, 2015 at 10:29 AM, peter dalgaard <pda...@gmail.com> wrote:
>
>>
>> On 19 Nov 2015, at 16:17 , C W <tmrs...@gmail.com> wrote:
>>
>>> Hi Rolf,
>>>
>>> I think the MLE should be 1.71, no? And yes, I am aware of the
>>> maximum=TRUE argument. I still feel something is wrong here.
>>>
>>
>> Just read more carefully what Rolf said: Your fn is MINUS the
>> log-likelihood. So the graph is upside-down.
>>
>> -pd
>>
>>
>>> Thanks!
>>>
>>> On Wed, Nov 18, 2015 at 6:23 PM, Rolf Turner <r.tur...@auckland.ac.nz>
>>> wrote:
>>>
>>>> On 19/11/15 11:31, C W wrote:
>>>>
>>>>> Dear R list,
>>>>>
>>>>> I am trying to find the MLE of the likelihood function. I will plot
>> the
>>>>> log-likelihood to check my answer.
>>>>>
>>>>> Here's my R code:
>>>>>
>>>>> xvec <- c(2,5,3,7,-3,-2,0)
>>>>>
>>>>> fn <- function(theta){
>>>>>
>>>>> sum(0.5 * (xvec - rep(theta, 7)) ^ 2 / 1 + 0.5 * log(1))
>>>>>
>>>>> }
>>>>>
>>>>> gn <- Vectorize(fn)
>>>>>
>>>>> curve(gn, -5, 20)
>>>>>
>>>>> optimize(gn, c(-5, 20))
>>>>>
>>>>> $minimum
>>>>>
>>>>> [1] 1.714286
>>>>>
>>>>> $objective
>>>>>
>>>>> [1] 39.71429
>>>>>
>>>>>
>>>>> The MLE using optimize() is 1.71, but what curve() gives me is the
>>>>> absolute
>>>>> minimum.
>>>>>
>>>>> I think 1.71 is the right answer, but why does the graph showing it's
>> the
>>>>> minimum? What is going on here?
>>>>>
>>>>
>>>> Your graph shows that there is indeed a *minimum* at 1.71. And
>> optimise()
>>>> is correctly finding that minimum.
>>>>
>>>> If you want optimise() to find the maximum, set maximum=TRUE. In which
>>>> case it will return "20" (or something very close to 20).
>>>>
>>>> Your function fn() appears not to be the log likelihood that you had in
>>>> mind. Perhaps you the negative of fn()???
>>>>
>>>> cheers,
>>>>
>>>> Rolf Turner
>>>>
>>>> --
>>>> Technical Editor ANZJS
>>>> Department of Statistics
>>>> University of Auckland
>>>> Phone: +64-9-373-7599 ext. 88276
>>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
>>> 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.
>>
>> --
>> Peter Dalgaard, Professor,
>> Center for Statistics, Copenhagen Business School
>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>> Phone: (+45)38153501
>> Office: A 4.23
>> Email: pd....@cbs.dk Priv: pda...@gmail.com
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> 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.
David Winsemius
Alameda, CA, USA
______________________________________________
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