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...

theory, the law of total variance or variance decomposition formula or conditional variance formulas or law of iterated variances also known as Eve's law...

the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error...

A conditional variance swap is a type of variance swap or swap derivative product that allows investors to take exposure to volatility in the price of...

all its random variables have the same finite variance; this is also known as homogeneity of variance. The complementary notion is called heteroscedasticity...

In probability theory, the conditional expectation, conditional expected value, or conditional mean of a random variable is its expected value evaluated...

In probability theory and statistics, variance is the expected value of the squared deviation from the mean of a random variable. The standard deviation...

corresponding names such as the conditional mean and conditional variance. More generally, one can refer to the conditional distribution of a subset of a...

inverting back to get the conditional covariance matrix. Note that knowing that x2 = a alters the variance, though the new variance does not depend on the...

matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between...