combined estimator
1James-Stein estimator — The James Stein estimator is a nonlinear estimator which can be shown to dominate, or outperform, the ordinary (least squares) technique. As such, it is the best known example of Stein s phenomenon.An earlier version of the estimator was… …
2Stein's example — Stein s example, sometimes referred to as Stein s phenomenon or Stein s paradox, is a surprising effect observed in decision theory and estimation theory. Simply stated, the example demonstrates that when three or more parameters are estimated… …
3Effect size — In statistics, an effect size is a measure of the strength of the relationship between two variables in a statistical population, or a sample based estimate of that quantity. An effect size calculated from data is a descriptive statistic that… …
4Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… …
5Channel state information — In wireless communications, channel state information (CSI) refers to known channel properties of a communication link. This information describes how a signal propagates from the transmitter to the receiver and represents the combined effect of …
6Social Security (United States) — This article is about the retirement/disability program. For the general concept of providing welfare, see Social security. For other uses, see Social Security (disambiguation) …
7Normal distribution — This article is about the univariate normal distribution. For normally distributed vectors, see Multivariate normal distribution. Probability density function The red line is the standard normal distribution Cumulative distribution function …
8Estimation of covariance matrices — In statistics, sometimes the covariance matrix of a multivariate random variable is not known but has to be estimated. Estimation of covariance matrices then deals with the question of how to approximate the actual covariance matrix on the basis… …
9Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… …
10Odds ratio — The odds ratio [1][2][3] is a measure of effect size, describing the strength of association or non independence between two binary data values. It is used as a descriptive statistic, and plays an important role in logistic regression. Unlike… …
