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Topic: Point estimation

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Point estimation

Estimator

Statistical inference

Data

Parameter

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	Overview of Point Estimation (Site not responding. Last check: 2007-09-17)
		When the estimate is a single number, the estimate is called a "point estimate"; when the estimate is a range of scores, the estimate is called an interval estimate.
		For example, a point estimate of the standard deviation is used in the calculation of a confidence interval for μ.
		Point estimates of parameters are often used in the formulas for significance testing.
	davidmlane.com /hyperstat/B12386.html (178 words)

	Point estimation - Wikipedia, the free encyclopedia
		In statistics, point estimation involves the use of sample data to calculate a single value (known as a statistic) which is to serve as a "best guess" for an unknown (fixed or random) population parameter.
		Point estimation should be contrasted with Bayesian methods of estimation, where the goal is usually to compute (perhaps to an approximation) the posterior distributions of parameters and other quantities of interest.
		The contrast here is between estimating a single point (point estimation), versus estimating a weighted set of points (a probability density function).
	en.wikipedia.org /wiki/Point_estimation (156 words)

	Parameter estimation
		The distinction between these two types of estimation is moot when the parameters in the mathematical expression of the family are properties of the distribution, as it is the case for example of the normal distribution (mean and variance).
		In a binormal distribution, the empirical correlation coefficient is a biased estimator of the coefficient of correlation of the distribution.
		An estimator is a statistic whose properties as a random variable let us expect that its value for the sample at hand (the estimate) is close to the true value of the parameter that is being estimated.
	www.aiaccess.net /English/Glossaries/GlosMod/e_gm_estimation.htm (2380 words)

	Computational Statistics: Single Point Estimation
		estimate for p>1 follows since the pth power of distance from each observation is a strictly convex function, the sum of strictly convex functions is convex, and a convex function has a unique minimum.
		Any point set has a center point, that is, a point x such that any halfspace that doesn't contain x can contain at most a constant fraction dn/(d+1) of the observations.
		All this has assumed that the distance between two points should be measured using the normal Euclidean distance, in which we square the difference in each coordinate, sum the squares, and take the square root of the sum.
	www.ics.uci.edu /~eppstein/280/point.html (1815 words)

	ESTIMATION
		The purpose of estimation is to estimate an unknown population parameter based on information gathered from a sample.
		Because estimation is based on a sample the estimation process is imprecise.
		Point Estimation is a procedure in which a precise value for the population parameter is calculated.
	otel.uis.edu /yoder/est_h.htm (581 words)

	Statistical Estimation in Neuroscience
		Estimating this f(y) is not fundamentally different from point estimation, as examined in Section 2 of this tutorial.
		This estimator, which we denote f**, is a smooth function which is known to approximate rather well the tuning curves of motor cortical neurons.
		In fact the bias is the difference between the expected value of the estimate (remember that the estimate is a random variable since it depends on the data D) and the true f(y).
	www.dam.brown.edu /people/elie/stats_tutorial.html (4827 words)

	Statistics Chapter 6 (Site not responding. Last check: 2007-09-17)
		Point estimation is an estimating procedure in which a single sample value (sample mean) is calculated as an estimate for its own population parameter
		In the point estimation, this single sample statistic is used as an estimate of the population parameter m
		an estimate of p or assume a value of p to be 1/2.
	facstaff.bloomu.edu /wblee/346pesti.htm (710 words)

	Visionary Tools - 3-Point-Estimating for Better Decisions
		Or the experienced person gave you estimates with exaggerated private (and hidden) reserves on cost and time, and you learn that Parkinson's law still applies that work is going to fill the time which has been assigned to it.
		An estimate may be optimistic, pessimistic or realistic, whatever this may mean.
		An estimate may be made according to a lot of experience or be just a ballpark number assigned to something yet unknown.
	www.visionarytools.com /decision-making/3-point-estimating.htm (1379 words)

	Function Point Analysis
		A function point is defined as one end-user business function, such as a query for an input.
		Currently, function point counting is a time-consuming and largely manual activity unless tools are built to assist the process.
		For estimation of effort, approaches based on lines of code (LOC) are an alternative.
	www.sei.cmu.edu /activities/str/descriptions/fpa_body.html (1152 words)

	Untitled Document
		This article presents a brief overview of the use case point estimation technique and includes an applet programme to allow you to perform a use case point based estimate for your current projects.
		Estimation by use case point analysis uses the project's expected functionality in the form of the use case model to define the actual project size.
		Use case point analysis was originally developed by Gustav Karner (1993) and later refined by Schneider and Winter (1998).
	www.liemur.com /Articles/UseCasePointEstimation.html (543 words)

	IT Project Estimation: Estimation References & Resources
		McConnell also seems keen to split "estimation" from "planning" - activities which go hand-in-hand in the world in which I live, particularly in early stages of a project when such things as function points and lines of code are not so easy to ascertain.
		Estimation Using Use-Case Points by Mel Damodaran and Aqua Netta E. Washington from The Proceedings of ISECON 2002 summarises the technique.
		On the website of Liemur Limited is a short article about use case point estimation and a free fully functional use case point estimation Java application for download.
	www.itprojectestimation.com /estrefs.htm (2645 words)

	451 Cost and Effort Estimation (Site not responding. Last check: 2007-09-17)
		Size estimation may involve estimation by analogy with other projects, estimation by ranking the sizes of system components and using a known reference component to estimate the component size or may simply be a question of engineering judgement.
		ESTIMACS is a "macro- estimation model" that uses a function point estimation method enhanced to accommodate a variety of project and personnel factors.
		This reinforces the fact that the output of estimation tools should be used as one "data point" from which estimates are derived--not as the only source for an estimate.
	ksi.cpsc.ucalgary.ca /courses/451-96/mildred/451/CostEffort.html (1621 words)

	Software Engineering: Function Point Analysis: Introduction
		The common method of estimation is to look for experience on similar projects in the past, either by consulting experts or looking at documentation on previous projects.
		Making an estimate of the number of lines of code in a new project requires experience, and can be very difficult for new applications.
		Function points don't solve the problems of team variation, programming tool variation, type of application, etc. There are 14 adjustment factors in the current IFPUG standard, but they may be eliminated from an upcoming ISO standard.
	leepoint.net /notes-java/principles_and_practices/fpa/fpa-intro.html (457 words)

	Dear Dr. Use Case: What About Function Points and Use Cases? (Site not responding. Last check: 2007-09-17)
		Function points rely heavily on the physical layout of the system (for example, numbers of tables and fields) and are therefore predominantly data driven.
		Although the early estimates you get with this technique can give you a good start, the most important thing to remember is that they are only gross estimates.
		Premature estimation is a very nasty condition that leads managers to commit the team to unrealistic budgets, which results in everyone on the project becoming hot under the collar, resources being spent before completion, and requirements that are only half satisfied.
	www-128.ibm.com /developerworks/rational/library/2870.html (2463 words)

	Coding Horror: How Long Would It Take if Everything Went Wrong? (Site not responding. Last check: 2007-09-17)
		When you compare the original single-point estimates to the Best Case and Worst Case estimates, you see that the 11.25 total of the single-point estimates is much closer to the Best Case estimate of 10.5 days than to the Worst Case total of 18.25 days.
		Three items were estimated to take less time in the best case, one was estimated to take more time in the best case, and six were estimated the same.
		So I think it supports the statement that single-point estimates tend to be best-case estimates, but I don't think it supports the statement that thinking about the worst case /always/ makes one gloomier about the best case.
	www.codinghorror.com /blog/archives/000611.html (1728 words)

	OECD Glossary of Statistical Terms - Estimation
		Estimation is concerned with inference about the numerical value of unknown population values from incomplete data such as a sample.
		Therefore the sample estimates need to be inflated to represent the whole population of interest.
		Estimation is the means by which this inflation occurs.
	stats.oecd.org /glossary/detail.asp?ID=860 (144 words)

	boiling point estimation
		The boiling point is defined as the temperature at which the
		For pure compounds, the normal boiling point is defined as the boiling point at one standard atmosphere of pressure on the liquid.
		, the boiling point observed for the compound differs from that estimated for the pure compound.
	www.pirika.com /chem/TCPEE/BP/ourBP.htm (228 words)

	IFPUG Bulletin Board: Function Point Estimation
		The average variance between estimating and counting was +/- 7 percent.
		Quick Function Point has an inbuilt maximum possible error of around 40% (you could count something as average complexity when it is really high complexity or when it was low complexity).
		Roughly 1991, a paper was published out of McDonnell Douglas called “FP-S Function Point Simplified.” It detailed their method of estimating function point counts with a small margin of error.
	www.ifpug.org /discus/messages/1778/7997.html?1158147346 (930 words)

	Supreme Court Ideology Project - Background Information
		Ideal point estimation is built on the idea that the ideology of each person (in our case, each Supreme Court justice) can be represented as a point, usually along a single line.
		The main objective of ideal point estimation is to obtain an estimated location for each justice on a liberal-conservative scale.
		In Bayesian statistics, we quantify our beliefs about the ideal points and other parameters of the model with probability distributions which tell us the probability that the parameters are within a given interval.
	www.stanford.edu /~tahk/sct/background.html (782 words)

	Function Point Estimation Methods: A Comparative Overview - Meli, Santillo (ResearchIndex) (Site not responding. Last check: 2007-09-17)
		Abstract: The appearance of the Function Point technique has allowed the ICT community to increase significantly the practice of software measurement, with respect to the use of the traditional "Lines of Code approach".
		There are at least two situations in which having an estimation method, compatible but alternative to...
		Meli, R., L. Santillo, "Function point estimation methods: a comparative overview", FESMA 98 - The European Software Measurement Conference -- Amsterdam, October 6-8, 1999.
	citeseer.ist.psu.edu /meli99function.html (373 words)

	Stereo Face Tracking and Gaze Point Estimation (Site not responding. Last check: 2007-09-17)
		As people interact face-to-face on a dailey basis they are constantly aware of where the other person's eyes are looking, indeed eye contact is a crucial part of effective communication.
		A vision system capable of tracking the human face and estimating the person's gaze point in real time offers many possiblilities for enhancing human-machine interaction.
		A key feature is such a system is its entirely non-intrusive nature, enabling people to be observed in their 'natural' state.
	users.rsise.anu.edu.au /~rsl/rsl_stfacetrack.html (477 words)

	Minimum Variance Unbiased Estimation (Site not responding. Last check: 2007-09-17)
		For example, the sample mean and sample median are both natural estimators of the mean of a normal population.
		We want our estimator to be like target 3: unbiased with the smallest possible variance.
		Thus, we only look at unbiased estimators and choose the one with the smallest variance.
	stat.tamu.edu /stat30x/notes/node100.html (130 words)

	Point Estimation (Site not responding. Last check: 2007-09-17)
		Next: Point Estimators for Different Up: Exam 1 and Point Previous: Schedule:
		Given a population parameter of interest, e.g., the population mean
		Estimator The statistic (formula) used to obtain the point estimate.
	www.stat.tamu.edu /stat30x/notes/node97.html (120 words)

	Poisson Change-point Procedure (Site not responding. Last check: 2007-09-17)
		Statistical methods for the estimation of the change-point in a Poisson process
		Enter the URL of the file containing your data.
		Continuous-time Estimation of a Change-point in a Poisson Process.
	www.stat.sc.edu /rsrch/gasp/poicha (59 words)

	IngentaConnect Change Point Estimation by Local Linear Smoothing (Site not responding. Last check: 2007-09-17)
		We consider the problem of estimating jump points in smooth curves.
		We focus essentially on the basic situation where a unique change point is present in the regression function.
		You will be able to remove this item from your shopping cart at any time before you have completed check-out.
	www.ingentaconnect.com /content/ap/mv/2002/00000083/00000001/art02038 (223 words)

	EconPapers: Point Estimation of Discrete Games (Site not responding. Last check: 2007-09-17)
		Abstract: We propose a method for point estimation of discrete games similar to those considered by Bresnahan and Reiss (1991).
		In the model, the vNM utilities are a function of observed co-variates and random preference shocks.
		We use recently developed computational methods to find all of the equilibrium (including mixed strategies) to the game.
	econpapers.repec.org /paper/redsed004/51.htm (220 words)

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