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Seen as a function of for given , (= | =) is a probability mass function and so the sum over all (or integral if it is a conditional probability density) is 1. Seen as a function of x {\displaystyle x} for given y {\displaystyle y} , it is a likelihood function , so that the sum (or integral) over all x {\displaystyle x} need not be 1.
Note: The conditional expected values E( X | Z) and E( Y | Z) are random variables whose values depend on the value of Z. Note that the conditional expected value of X given the event Z = z is a function of z. If we write E( X | Z = z) = g(z) then the random variable E( X | Z) is g(Z). Similar comments apply to the conditional covariance.
The following formula shows how to apply the general, measure theoretic variance decomposition formula [4] to stochastic dynamic systems. Let Y ( t ) {\displaystyle Y(t)} be the value of a system variable at time t . {\displaystyle t.}
Use of a user-defined function sq(x) in Microsoft Excel. The named variables x & y are identified in the Name Manager. The function sq is introduced using the Visual Basic editor supplied with Excel. Subroutine in Excel calculates the square of named column variable x read from the spreadsheet, and writes it into the named column variable y.
where () = [= ()] and = is the Fisher information of Y relative to calculated with respect to the conditional density of Y given a specific value X = x. As a special case, if the two random variables are independent , the information yielded by the two random variables is the sum of the information from each random variable separately:
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Use of named column variables x & y in Microsoft Excel. Formula for y=x 2 resembles Fortran, and Name Manager shows the definitions of x & y. In most implementations, a cell, or group of cells in a column or row, can be "named" enabling the user to refer to those cells by a name rather than by a grid reference.