allocateDelta: Allocate Delta via Maximum Likelihood
In SWS-Methodology/faoswsAupus: Package to perform the AUPUS calculation.

Description Usage Arguments Details Value

This function assumes that a sum of several elements has been updated and that the adjustment must be split up into each of the individual elements in the sum. Thus, we start with an equation like:

1	allocateDelta(param1, param2, dist = rep("Normal", length(param1)), sign)

`param1`	A vector of the first parameter for each of the elements. For a normal distribution, this is the mean.
`param2`	A vector of the second parameter for each of the elements. For a normal distribution, this is the standard deviation.
`dist`	A vector of the name of the distribution for each distribution. Currently, only "Normal" is implemented.
`sign`	A vector of the sign of each element. These values should all be +1 or -1, and they indicate if Delta_1, Delta_2, ... should be pre-multiplied by a negative or not. Usually, these will all be +1.

X_1 + X_2 + ... + X_N = Y

Y becomes Y + Delta, and we must determine a new equation such that

(X_1 + Delta_1) + (X_2 + Delta_2) + ... + (X_N + Delta_N) = Y + Delta

The individual delta values should be determined via maximum likelihood, as we have a distribution for each of these elements. We can simplify the problem a bit by subtracting Y from both sides:

Delta_1 + Delta_2 + ... + Delta_N = Delta

A vector of the final values (Delta_1, Delta_2, ..., Delta_N)

SWS-Methodology/faoswsAupus documentation built on May 9, 2019, 11:45 a.m.