log(f) with respect to a predefined set of variables/variable combinations.DerivLogf(f, names, map = NULL, yMap = NULL, thetaMap = NULL)Deriv2Logf(f, names, map = NULL, yMap = NULL, thetaMap = NULL)
a="b" => a <- b).map with a=b resolving to a <- y[b].map with a=b resolving to a <- theta[[b]].DerivLogf returns function(y, theta, i, ...) where theta is a list of parameters.
It evaluates to the first derivative of log(f) with respect to variable i.
Additionally the attribute "d" contains the list of sub functions.Deriv2Logf returns function(y, theta, i, j, ...) where theta is a list of parameters.
It evaluates to the second derivative of log(f) with respect to the variables i and j.
Additionally the attribute "d2" contains the list of sub functions.
numDerivLogf relies on DerivLogf utilizes Deriv to build sub functions for each variable in names.
The same is true for Deriv2Logf.Deriv won't recognize components or parameters accessed by [, [[ or $ as variables (e.g. theta[["beta1"]]).
Therefore it's necessary to specify mappings from y and theta to the variables in f.
Deriv in package buildf, numDerivLogf, fisherI## see examples for param
## mind the gain regarding runtime compared to numDerivRun the code above in your browser using DataLab