estimate

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Related to estimator: Unbiased estimator

ballpark estimate

An approximate estimate. Mary contacted several plumbers to get a ballpark estimate of the cost to fix her leaky toilet.
See also: ballpark, estimate

estimate the cost at (something)

To predict that something will cost a certain amount. Unfortunately, I would estimate the cost of these car repairs at $1,000.
See also: cost, estimate

estimate the cost at

(some amount) to approximate the cost of something at a particular amount. I estimate the cost at about one hundred dollars. The cost of repairing the car was estimated at over four thousand dollars!
See also: cost, estimate

a ballpark figure

or

a ballpark estimate

A ballpark figure or a ballpark estimate is an approximate figure or quantity. Note: A ballpark is a park or stadium where baseball is played. But what are we talking about here — a few thousand, millions, two bucks? Give me a ballpark figure. I think just in a ballpark estimate — about 60-40. Sixty would support, 40 percent would be opposed.
See also: ballpark, figure

a ˈballpark figure

a number which is approximately correct: I know we haven’t really discussed costs yet, but can you give me a ballpark figure?
See also: ballpark, figure
References in periodicals archive ?
This estimator combines the characteristics of DA and NDA estimators such that the signal packet used for estimation contains both pilot and data symbols.
Bias and Mean square error of ratio type variance estimator was (Eq.
For pricing, the estimator has to rely on experience and historical data unlike a contractor's estimator who has the actual price from the subcontractors and vendors.
In the present article, we have proposed a class of ratio estimators for the estimation of finite population mean using simple random sampling scheme when there is maximum and minimum values on both the study and the aux iliary variables and their properties are considered up to the first order of approximation.
State estimators help in monitoring, controlling, and supervising of transmission and distribution networks.
Cost estimators can also provide improved decision support with a better understanding of group dynamics.
It can be noted that although both estimators are very close to the theoretical one, the K phase estimator seems to have an error smaller than the K power estimator.
For this estimator (referred to as the "DS"), volume-predicted mortality (hospitals' expected mortality rate given their volume) and observed hospital-specific mortality are calculated for each hospital, and these two inputs are weighted based on the reliability of the latter measure.
We're focusing on compliance, and the Adherence Estimator allows us to efficiently determine if someone is a low-, medium- or high-risk patient.
Moreover, as different populations have different species-abundance distributions, the estimator performance should depend also on the species-abundance distribution of the data set (Bunge & Fitzpatrick, 1993; Soberon & Llorente, 1993; Colwell & Coddington, 1994; Walter & Morand, 1998).
The net result of all these studies has been to show that there exist no clear guidelines for the choice of an estimator for econometric models.
The main objectives of the present study were: a) describe several lag-one autocorrelation estimators, presenting the expressions for their calculus; b) propose a new estimator and test it in comparison with the previously developed estimators in terms of bias and Mean Square Error (hereinafter, MSE); c) estimate the statistical power of the tests associated with the ten estimators and based on Monte Carlo sampling.
Finally, they use Monte Carlo simulation based on observed data to explore the performance of RD estimators with a forcing variable which is standardized within schools by choosing a different cutoff in each school.