Thanks Rolf. That took care of it. It should be lower=FALSE through right?
I want the upper tail because my values are right censored?
Regards,
Jake


On Fri, Apr 25, 2014 at 12:50 AM, Rolf Turner <r.turner@auckland.ac.nz>wrote:

>
> As usual I am too lazy to fight my way through the rather convoluted code
> presented, but it seems to me that you just want to calculate a log
> likelihood.  And that is bog-simple:
>
> The log likelihood for i.i.d. data is just the sum of log f(y_i) where the
> y_i are your observed values and f() is the density function of the
> distribution that you have in mind.
>
> Where there is (right) censoring you take the sum of log f(y_i) over all
> the non-censored values and then add k*(1-F(cens.time)) where k is the
> number of censored values and F() is the cumulative distribution function
> corresponding to f().
>
> In your case it would appear that f(y) = dlnorm(y,1.66,0.25) and
> F(y) = plnorm(y,1.66,0.25).  Note that instead of using 1-F(cens.time) you
> can use plnorm(cens.time,1.66,0.25,lower=TRUE) and that instead of taking
> logs explicitly you can set log=TRUE in the calls to dlnorm() and plnorm().
>
> cheers,
>
> Rolf Turner
>
>
> On 25/04/14 07:27, Jacob Warren (RIT Student) wrote:
>
>> I'm trying to figure out if there is a way in R to get the loglikelihood
>> of
>> a distribution fit to a set of data where the parameter values are fixed.
>> For example, I want to simulate data from a given alternate lognormal
>> distribution and then I will fit it to a lognormal distribution with null
>> parameter values to see what the likelihood of the null distribution is
>> given random data from the alternate distribution.
>>
>> I have been using fitdistrplus for other purposes but I cannot use it to
>> fix both parameter values.
>>
>> Here is an example of what I've been working with...
>>
>> nullmu<-1.66 #set null mu
>> altmu<-1.58 #set alt mu
>> sd.log<-0.25 #set common sigma
>> cens.time<-6 #if simulated times are greater than this turn them into
>> right
>> censored times
>>
>> #simulating lognormal data (time) from altnative dist
>> (sim<-rlnorm(n=samplesize, meanlog=altmu, sdlog=sd.log))
>> #if the time was > cens.time replace time with cens.time
>> (sim[which(sim>cens.time)]<-cens.time)
>> sim
>>
>> #create a variable indicating censoring
>> (cens<-sim)
>> cens[which(sim==cens.time)]<-NA
>> cens
>>
>> #create the data frame to be passed to fitdistcens and fitdist
>> (x<-data.frame(left=sim,right=cens))
>>
>>
>> #if there is censored data use fitdistcens else use fitdist
>> ifelse(length(which(is.na(cens)))>0,
>> simfit<-fitdistcens(censdata=x, distr="lnorm"),
>> simfit<-fitdist(data=x[,1], distr="lnorm")
>> )
>>
>> #Now I can get the loglikelihood of the MLE fitted distribution
>> simfit$loglik
>>
>> #I want to get the loglikelihood of the distribution with the null
>> parameterization
>> #This is what I can't get to work
>> #I can't seem to find any function that allows me to set both parameter
>> values
>> #so I can get to loglikelihood of the of the parameterization given the
>> data
>> nulldist<-fitdistcens(censdata=x, distr="lnorm",
>> start=list(meanlog=nullmu,
>> sdlog=sd.log)
>>
>> #Then I want to do a likelihood ratio test between the two distributions
>> pchisq((-2*simfit$loglik--2*nulldist$loglik), df=2, lower.tail=FALSE)
>>
>
>

	[[alternative HTML version deleted]]

