Displaying 2 results from an estimated 2 matches for "sum_k".
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2003 Jul 17
3
Looking to maximize a conditional likelihood
...in the i'th cluster It has vector covariates X_ij. c_ij is a
transform of y_ij and is in (0, 1) (it's actually the probability of
being in cluster j). It may be specified a priori or to be estimated.
Maximize the product over i of
c_ij exp(sum_j y_ij X_ij b)
----------------------------
sum_K c_ij exp(sum_K y_ij X_ij b)
Where sum_K means we are summing over all possible subsets of the strata
that contain the observed number of successes.
b, and perhaps c, are the parameters to estimate.
The more vanilla case has no c_ij terms. That says we maximize the
probability of the observed out...
2002 Dec 09
2
Sth better than cycle?
Hi,
I want to calculate expected likelihood over a 2D discrete
distribution, something like
\sum_k \sum_l p_{kl} L(v_k, v_l)
It is trivial to write a cycle like
for(k in 1:K)
for(l in 1:L)
sum <- sum + p[k,l]*L(v[k], v[l])
But is there a more clever way for R?
Best wishes,
Ott