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- What is the relation between estimator and estimate?
In Lehmann's formulation, almost any formula can be an estimator of almost any property There is no inherent mathematical link between an estimator and an estimand However, we can assess--in advance--the chance that an estimator will be reasonably close to the quantity it is intended to estimate
- Variance of sample median - Cross Validated
The HL median estimate is especially simple for small samples of size n, just compute all possible two point (including repeats) averages From these n(n+1) 2 new constructs, compute the HL Median Estimator as the usual sample median Now, per the same Wikipedia article on the median, the cited variance of the median 1 (4*n*f(median)*f(median))
- Notation in statistics (parameter estimator estimate)
We use an estimator which books usually denote by $\widehat{\theta}$ The estimator is a random variable
- ML vs WLSMV: which is better for categorical data and why?
The most common estimator used for this approach is some form of diagonally weighted least squares (DWLS) WLSMV falls under the DWLS umbrella, though it is not technically an estimator DWLS is the estimator, and calling WLSMV in a software package (e g , lavaan or Mplus ) tells the program to report robust standard errors and to use a
- What is the difference between estimation and prediction?
purpose: an estimator seeks to know a property of the true state of nature, while a prediction seeks to guess the outcome of a random variable; and uncertainty: a predictor usually has larger uncertainty than a related estimator, due to the added uncertainty in the outcome of that random variable Well-documented and -described predictors
- How to calculate the expected value of an estimator?
$\begingroup$ Found 6th edition from 25 yrs ago Same topic still in Ch6, Sect 1 This edition does not show how to find expectation of a random variable, but states sample mean $\bar X = \frac{\sum X}{n}$ may be used to estimate population mean $\mu $ Also, says sample median might be used
- estimation - The distribution of an estimator - Cross Validated
The bootstrap will approximate the sampling distribution for the m-estimator at the given fixed sample size It is an approximate method and we say the bootstrap works if we can show consistency theoretically $\endgroup$
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