search for: _weighted_

...(column), by subtracting the variable's mean value and dividing by the variable's mean absolute deviation. This works well when input variables are all in the same units. When I include new variables with a different intrinsic range, the ones with the largest relative values tend to be _weighted_ . this is certainly not surprising, but complicates things. Does there exist a robust technique to effectively re-scale each of the variables, regardless of their intrinsic range to some set range, say from {0,1} ? I have tried dividing a variable by the maximum value of that variable, but I...

...39; object, `x' is the independent variable vector, `yfit' the corresponding model prediction (`fitted(res)'), `se.fit' the corresponding standard error and `luconf' the lower and upper confidence limits at some level specified by `probex'. when using the same approach with _weighted_ fits (even if all weights are equal (but not equal to one)), I noted that the confidence limits depend on the weights in an counter-intuitive, probably erroneous way. I have tracked my problem down to the fact that `res$m$gradient()' does _not_ contain the actual gradients w.r.t. the parameter...