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Law of the unconscious statistician: The expected value of a measurable function of , (), given that has a probability density function (), is given by the inner product of and : [34] [()] = (). This formula also holds in multidimensional case, when g {\displaystyle g} is a function of several random variables, and f {\displaystyle f} is ...
In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated with respect to the conditional probability distribution. If the random variable can take on only a finite number of values, the "conditions" are that the variable can only take on a subset of ...
This results from the fact that the derivative of the exponential function e rx is a multiple of itself. Therefore, y′ = re rx, y″ = r 2 e rx, and y (n) = r n e rx are all multiples. This suggests that certain values of r will allow multiples of e rx to sum to zero, thus solving the homogeneous differential equation. [5]
The moment generating function of a real random variable is the expected value of , as a function of the real parameter . For a normal distribution with density f {\textstyle f} , mean μ {\textstyle \mu } and variance σ 2 {\textstyle \sigma ^{2}} , the moment generating function exists and is equal to
The reason why there is no analog of mean value equality is the following: If f : U → R m is a differentiable function (where U ⊂ R n is open) and if x + th, x, h ∈ R n, t ∈ [0, 1] is the line segment in question (lying inside U), then one can apply the above parametrization procedure to each of the component functions f i (i = 1 ...
The characteristic function of a uniform U(–1,1) random variable. This function is real-valued because it corresponds to a random variable that is symmetric around the origin; however characteristic functions may generally be complex-valued. In probability theory and statistics, the characteristic function of any real-valued random variable ...
An initial value problem is a differential equation ′ = (, ()) with : where is an open set of , together with a point in the domain of (,),called the initial condition.. A solution to an initial value problem is a function that is a solution to the differential equation and satisfies
The value function of an optimization problem gives the value attained by the objective function at a solution, while only depending on the parameters of the problem. [1] [2] In a controlled dynamical system, the value function represents the optimal payoff of the system over the interval [t, t 1] when started at the time-t state variable x(t)=x. [3]