What is the difference between an estimator and a statistic?
An "estimator" or "point estimate" is a statistic (that is, a function of the data) that is used to infer the value of an unknown parameter in a statistical model. So a statistic refers to the data itself …
What is the relation between estimator and estimate?
Feb 24, 2011 · While estimator is your data, which is also a random variable. For different types of distributions you have different types of data and thus you have a different estimate and thus …
What is the difference between a consistent estimator and an …
An estimator is unbiased if, on average, it hits the true parameter value. That is, the mean of the sampling distribution of the estimator is equal to the true parameter value.
Notation in statistics (parameter/estimator/estimate)
Aug 2, 2018 · We use an estimator which books usually denote by θˆ θ ^. The estimator is a random variable! Usually we seek E[θˆ] = θ E [θ ^] = θ and so on and on, anyways. An …
Estimator for a binomial distribution - Cross Validated
Oct 7, 2011 · How do we define an estimator for data coming from a binomial distribution? For bernoulli I can think of an estimator estimating a parameter p, but for binomial I can't see what …
random variable - When is the median-of-means estimator better …
May 22, 2023 · The median-of-means estimator is often given as an alternative way to, given a sequence of IID random variables X1,...,XN X 1,, X N, estimate the expectation value E[X] E …
Why is it important that estimators are unbiased and consistent?
But it is a property that requires very strong conditions, and even a little non-linearity in the estimator expression may destroy it. Consistency is important mainly with observational data …
ML vs WLSMV: which is better for categorical data and why?
I was wondering which is a better estimator to use for categorical data: ML or WLSMV. I saw on a discussion on the Mplus website that they recommend WLSMV for categorical data but didn't …
When is a maximum likelihood estimator biased? [duplicate]
Feb 25, 2025 · It is known that maximum likelihood estimators (MLE) can be biased. Can we predict whether a given distribution and parameter of interest will produce a biased MLE? On …
Is it ever preferable to have an estimator with a larger variance?
Mar 21, 2025 · In statistics, a common way to judge the quality of an estimator is by its variance - an estimator is said to be better if the variance of the estimator is smaller. For example, if we …