Displaying 5 results from an estimated 5 matches for "_sum_".
Did you mean:
sum_
2006 Nov 15
1
OPTIM--non finite finite different [13]
Dear All:
I used optim() to minimise the loglikelihood function for fitting data to negative binomial distribution. But there initial value of log-likelihood and iteration 10 value are reasonable. for example:
initial value 1451657.994524
iter 10 value 47297.534905
iter 20 value -623478636.8236478
Then the iter 20 vlaue suddelnly changes to a negative value and in the end the error mesage is
2008 Dec 26
1
histogramm$density
hello,
i am using the hist function with classified values. The class breaks are >1, so
histogram$density is != 1.
How to plot the histogram with freq=FALSE and the real class density values.
I used:
> h2 = hist(value, breaks = breaks_vector)
> h2$density = round(h2$counts/sum(h2$counts), 2)
> h2$intensities = h2$density
> plot(h2, freq=F)
but this isn't the best way, i
2009 Oct 28
1
cross-over designs
Hi,
I have a dataset from a client where the data is from a cross-over
design. Basically, each subject in a survey was asked to rate two
products, A and B. The subject sampled A first and then after an
appropriate wash-out period he/she sampled B. The next subject did the
same, but in a different order. How can I do an ANOVA analysis on a
cross-over design with only two treatments. This
2011 Jul 15
2
scaling advice
Hi,
I have a consultants nightmare -- I was given a project that another
consultant did and I was told to do the same calculations, but there's
no documentation on what he did. Basically, I have yes/no answers to
survey questions about the effectiveness of product attributes by
brands. There are 44 attributes and 13 brands. The other guy scaled
the proportion of respondents who said
2004 Nov 13
3
density estimation: compute sum(value * probability) for given distribution
Dear R users,
This is a KDE beginner's question.
I have this distribution:
> length(cap)
[1] 200
> summary(cap)
Min. 1st Qu. Median Mean 3rd Qu. Max.
459.9 802.3 991.6 1066.0 1242.0 2382.0
I need to compute the sum of the values times their probability of
occurence.
The graph is fine,
den <- density(cap, from=min(cap),
to=max(cap), give.Rkern=F)