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...

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

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

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

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

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...

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

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

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...

In statistics and machine learning, the bias–variance tradeoff describes the relationship between a model's complexity, the accuracy of its predictions...

In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption...

the conditional variance of the outcome is not scalable to the identity matrix. When the conditional variance is known, then the inverse variance weighted...

swap, conditional variance swap, corridor variance swap, forward-start variance swap, option on realized variance and correlation trading. "Variance and...

Hierarchical linear modeling Fixed effects MINQUE Covariance estimation Conditional variance Panel analysis Baltagi, Badi H. (2008). Econometric Analysis of Panel...

In mathematics, more specifically in the theory of Monte Carlo methods, variance reduction is a procedure used to increase the precision of the estimates...

law of total variance. Some writers on probability call this the "conditional covariance formula" or use other names. Note: The conditional expected values...

the minimum-variance mean (for large normal samples), which is to say the variance of the median will be ~50% greater than the variance of the mean....

Y-chromosomal DNA. In the Wright-Fisher idealized population model, the conditional variance of the allele frequency p ′ {\displaystyle p'} , given the allele...

financial instruments. These are volatility swaps, variance swaps, conditional variance swaps, variance options, VIX futures for equities, and (with some...

expectation Conditional independence Conditional probability Conditional probability distribution Conditional random field Conditional variance Conditionality principle...

testing (FAST) is a variance-based global sensitivity analysis method. The sensitivity value is defined based on conditional variances which indicate the...

a linear function of X {\displaystyle \mathbf {X} } and that the conditional variance of the error term given X {\displaystyle \mathbf {X} } is a known...

Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between...

of the description of utility of stock holding to the expected mean and variance of the returns of the portfolio. In reality, there may be other utility...

population, data set, or probability distribution is the square root of its variance. It is algebraically simpler, though in practice less robust, than the...

Variance-based sensitivity analysis (often referred to as the Sobol’ method or Sobol’ indices, after Ilya M. Sobol’) is a form of global sensitivity analysis...

Derivative (finance) Options Swaps Amortising Asset Basis Commodity Conditional variance Constant maturity Correlation Credit default Currency Dividend Equity...

the sum of the bias and the variance of the learning algorithm. Generally, there is a tradeoff between bias and variance. A learning algorithm with low...

Jaehyuk; Wu, Lixin (July 2021). "The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model". Journal...