- estimation of parameters
- estimation of parameters STAT Parameterschätzung f (statistics)
Englisch-Deutsch Fachwörterbuch der Wirtschaft . 2013.
Englisch-Deutsch Fachwörterbuch der Wirtschaft . 2013.
Estimation theory — is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data. The parameters describe an underlying physical setting in such a way that the value of the parameters affects… … Wikipedia
Estimation of signal parameters via rotational invariant techniques — In estimation theory, estimation of signal parameters via rotational invariant techniques (ESPRIT) is a technique to determine parameters of a mixture of sinusoids in a background noise. References * … Wikipedia
List of digital estimation techniques — *Linear models **Parameter Estimation ***Deterministic parameters ****Least squares (batch and recursive processing) ****Best linear unbiased estimation (BLUE) ****Maximum likelihood ***Random parameters ****Mean squared ****Maximum a posteriori… … Wikipedia
Maximum spacing estimation — The maximum spacing method tries to find a distribution function such that the spacings, D(i), are all approximately of the same length. This is done by maximizing their geometric mean. In statistics, maximum spacing estimation (MSE or MSP), or… … Wikipedia
Location estimation in sensor networks — Location estimation in wireless sensor networks is the problem of estimating the location of an object from a set of noisy measurements, when the measurements are acquired in a distributedmanner by a set of sensors.MotivationIn many civilian and… … Wikipedia
Software development effort estimation — is the process of predicting the most realistic use of effort required to develop or maintain software based on incomplete, uncertain and/or noisy input. Effort estimates may be used as input to project plans, iteration plans, budgets, investment … Wikipedia
Rasch model estimation — Various techniques are employed in order to estimate parameters of the Rasch model from matrices of response data. The most common approaches are methods of maximum likelihood estimation, such as joint and conditional maximum likelihood… … Wikipedia
Spectral density estimation — In statistical signal processing, the goal of spectral density estimation is to estimate the spectral density (also known as the power spectrum) of a random signal from a sequence of time samples of the signal. Intuitively speaking, the spectral… … Wikipedia
Algorithme a estimation de distribution — Algorithme à estimation de distribution Les algorithmes à estimation de distribution résolvent des problèmes d optimisation en échantillonnant un modèle de distribution, dont les paramètres évoluent via des opérateurs de sélection. Ici, un AED à… … Wikipédia en Français
Algorithme À Estimation De Distribution — Les algorithmes à estimation de distribution résolvent des problèmes d optimisation en échantillonnant un modèle de distribution, dont les paramètres évoluent via des opérateurs de sélection. Ici, un AED à distribution normale mono variante… … Wikipédia en Français
Algorithme à estimation de distribution — Les algorithmes à estimation de distribution résolvent des problèmes d optimisation en échantillonnant un modèle de distribution, dont les paramètres évoluent via des opérateurs de sélection. Ici, un AED à distribution normale mono variante… … Wikipédia en Français