Description Usage Arguments Details Value
A function that use the arguments of a glm.cmp
call to generate a better initial
nu
estimate.
1 2 3 4 5 6 7 8 9 10 11 12 13 |
param |
numeric vector: the model coefficients & the current value of |
y |
numeric vector: response variable |
xx |
numeric matrix: the explanatory variables |
offset |
numeric vector: a vector of length equal to the number of cases |
llstart |
numeric: current log-likelihood value |
fsscale |
numeric: a scaling factor (generally >1) for the relaxed fisher scoring algorithm |
lambdalb, lambdaub |
numeric: the lower and upper end points for the interval to be searched for lambda(s). |
maxlambdaiter |
numeric: the maximum number of iterations allowed to solve for lambda(s). |
tol |
numeric: the convergence threshold. A lambda is said to satisfy the mean constraint if the absolute difference between the calculated mean and a fitted values is less than tol. |
summax |
maximum number of terms to be considered in the truncated sum |
From version 0.3.4, this function is no longer being used as part of the estimation algorithm and this function will be defunct in our next update.
List containing the following:
param |
the model coefficients & the updated |
maxl |
the updated log-likelihood |
fsscale |
the final scaling factor used |
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