The ratio estimator is a statistical estimator for the ratio of means of two random variables. Ratio estimates are biased and corrections must be made when they are used in experimental or survey work. The ratio estimates are asymmetrical and symmetrical tests such as the t test should not be used to generate confidence intervals.
The bias is of the order O(1/n) (see big O notation) so as the sample size (n) increases, the bias will asymptotically approach 0. Therefore, the estimator is approximately unbiased for large sample sizes.
The ratioestimator is a statistical estimator for the ratio of means of two random variables. Ratio estimates are biased and corrections must be made...
In statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter...
Price–performance ratio Proportionality (mathematics) Ratio distribution Ratioestimator Rate (mathematics) Ratio (Twitter) Rate ratio Relative risk Rule...
address limitations of the sample odds ratio. One alternative estimator is the conditional maximum likelihood estimator, which conditions on the row and column...
to the standard unbiased variance estimator. Proof The Taylor linearization states that for a general ratioestimator of two sums ( R ^ = Y ^ Z ^ {\displaystyle...
of return per unit, gives a rate of return. The accuracy of Sharpe ratioestimators hinges on the statistical properties of returns, and these properties...
Shrinkage estimator Sichel distribution Siegel–Tukey test Sieve estimator Sigma-algebra SigmaStat – software Sign test Signal-to-noise ratio Signal-to-noise...
statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average...
Hodges–Lehmann estimator is a robust and highly efficient estimator of the population median; for non-symmetric distributions, the Hodges–Lehmann estimator is a...
distribution (also known as reciprocal distribution) Product distribution Ratioestimator Slash distribution Note, however, that X 1 {\displaystyle X_{1}} and...
first known use of a ratioestimator. Laplace in 1802 estimated the population of France with a similar method; see Ratioestimator § History for details...
maximum likelihood estimator. s n ( θ ) = 0 {\displaystyle s_{n}(\theta )=\mathbf {0} } In that sense, the maximum likelihood estimator is implicitly defined...
on the variance of an estimator for some parameter of a population. It is calculated as the ratio of the variance of an estimator based on a sample from...
In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value...
estimates. Unfortunately, when there are outliers in the data, classical estimators often have very poor performance, when judged using the breakdown point...
can be solved analytically; for instance, the ordinary least squares estimator for a linear regression model maximizes the likelihood when the random...
the statistical sense. Margin of error Propagation of uncertainty Ratioestimator Sampling (statistics) Wikimedia Commons has media related to Sampling...
square error (MMSE) estimator is an estimation method which minimizes the mean square error (MSE), which is a common measure of estimator quality, of the...
estimation. The GMM estimators are known to be consistent, asymptotically normal, and most efficient in the class of all estimators that do not use any...
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