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In probability theory and statistics, a conditional variance is the variance of a random variable given the value(s) of one or more other variables. Particularly in econometrics , the conditional variance is also known as the scedastic function or skedastic function . [ 1 ]
Let Y be a random variable and X another random variable on the same probability space. The law of total variance can be understood by noting: The law of total variance can be understood by noting: Var ( Y ∣ X ) {\displaystyle \operatorname {Var} (Y\mid X)} measures how much Y varies around its conditional mean E [ Y ∣ X ...
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 ...
However, it can be bounded by coherent risk measures like Conditional Value-at-Risk (CVaR) or entropic value at risk (EVaR). CVaR is defined by average of VaR values for confidence levels between 0 and α. However VaR, unlike CVaR, has the property of being a robust statistic. A related class of risk measures is the 'Range Value at Risk' (RVaR ...
the conditional operator can yield a L-value in C/C++ which can be assigned another value, but the vast majority of programmers consider this extremely poor style, if only because of the technique's obscurity. [6]
^c The ALGOL 68, C and C++ languages do not specify the exact width of the integer types short, int, long, and (C99, C++11) long long, so they are implementation-dependent. In C and C++ short , long , and long long types are required to be at least 16, 32, and 64 bits wide, respectively, but can be more.
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 above example takes the conditional of Math.random() < 0.5 which outputs true if a random float value between 0 and 1 is greater than 0.5. The statement uses it to randomly choose between outputting You got Heads! or You got Tails! to the console. Else and else-if statements can also be chained after the curly bracket of the statement ...