conditional density function

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• Conditional probability distribution — Given two jointly distributed random variables X and Y, the conditional probability distribution of Y given X is the probability distribution of Y when X is known to be a particular value. If the conditional distribution of Y given X is a… …   Wikipedia

• Density estimation — In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to… …   Wikipedia

• Conditional expectation — In probability theory, a conditional expectation (also known as conditional expected value or conditional mean) is the expected value of a real random variable with respect to a conditional probability distribution. The concept of conditional… …   Wikipedia

• Likelihood function — In statistics, a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of …   Wikipedia

• Marginal conditional stochastic dominance — In finance, marginal conditional stochastic dominance is a condition under which a portfolio can be improved in the eyes of all risk averse investors by incrementally moving funds out of one asset (or one sub group of the portfolio s assets) and… …   Wikipedia

• Minkowski's question mark function — Minkowski question mark function. ?(x) is on the left and ?(x) x is on the right. In …   Wikipedia

• Radial basis function network — A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. They are used in function approximation, time series prediction, and control.Network architectureRadial basis function (RBF) …   Wikipedia

• Errors-in-variables models — In statistics and econometrics, errors in variables models or measurement errors models are regression models that account for measurement errors in the independent variables. In contrast, standard regression models assume that those regressors… …   Wikipedia

• Stochastic kernel estimation — In statistics, a stochastic kernel estimate is an estimate of the transition function of a (usually discrete time) stochastic process. Often, this is an estimate of the conditional density function obtained using kernel density estimation. The… …   Wikipedia

• CDF — choledochoduodenal fistula; chondrodystrophia foetalis; class conditional density function; clinical data field; clinical data framework; common data format; cumulative distribution function; [poly] chlorinated dibenzofuran * * * cumulative… …   Medical dictionary

• CDF — • choledochoduodenal fistula; • chondrodystrophia foetalis; • class conditional density function; • clinical data field; • clinical data framework; • common data format; • cumulative distribution function; • [poly] chlorinated dibenzofuran …   Dictionary of medical acronyms & abbreviations