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Everything about Point estimation
Parameter estimation via sample statistics
In statistics, point estimation involves the use of sample data to calculate a single value, which serves as a "best guess" or "best estimate" of an unknown quantity, for example, the population mean, the variance of a distribution, or a model parameter. Wikipedia →
🧠Start here: a 6-step reading path
- Read the overview: Point estimationA 5-minute orientation
- Skim a recent paper: GPT2SP: A Transformer-Based Agile Story Point Estimation ApproachInfluential work since 2022
- Pick up a classic book: Theory of point estimationThe most-reprinted book on the subject
- Read the landmark paper: Pose estimation from corresponding point dataCited 469 times
- Go sideways: MINQUEA closely related topic
- Go sideways: Lehmann–Scheffé theoremA closely related topic
đź“– Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Pose estimation from corresponding point data
Nonparametric Change-Point Estimation
Change point estimation using nonparametric regression
Estimation of a truncation point
ON CHANGE POINT DETECTION AND ESTIMATION
Estimation of flash point
Point Estimation Following Group Sequential Tests
REMARKS ON SEQUENTIAL POINT ESTIMATION
🆕 Influential since 2022
GPT2SP: A Transformer-Based Agile Story Point Estimation Approach
GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation
PT-FlowNet: Scene Flow Estimation on Point Clouds With Point Transformer
IQ Skew and Imbalance Estimation for Coherent Point-to-Multi-Point Optical Networks
Efficient Vanishing Point Estimation for Accurate Camera Rotation Estimation in Indoor Environments
đź“š Books worth reading
Theory of point estimationE. L. Lehmann · 1983
Distribution-free statistical methodsJ. S. Maritz · 1981- 📕Minimax solutions in sampling from finite populationsSiegfried Gabler · 1990
Unbiased estimators and their applicationsV. G. Voinov, V.G. Voinov · 1993
Cost estimates for the Boston planBoston (Mass.) · 1977- 📕Statistical inference for a family of counting processesOdd Olai Aalen · 1976
- 📕Theory of point estimationErich Leo Lehmann · 1983
Theory of point estimation · 2003
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
đź”— Related topics
- MINQUE In statistics, the theory of minimum norm quadratic unbiased estimation (MINQUE) was developed by C. R. Rao. MINQUE is a theory alongside other estimation…
- Lehmann–Scheffé theorem In statistics, the Lehmann–Scheffé theorem provides sufficient conditions for the existence of a best unbiased estimator in a statistical model. The theorem…
- Parametric statistics Parametric statistics is a branch of statistics that is concerned with the analysis of and inference from data assuming that the underlying distribution…
- Cross-entropy method The cross-entropy (CE) method is a Monte Carlo method for importance sampling and optimization. It is applicable to both combinatorial and continuous problems…
- Cramér–Rao bound In estimation theory and statistics, the Cramér–Rao bound (CRB) relates to estimation of a deterministic (fixed, though unknown) parameter. The result…
- Method of moments (statistics) In statistics, the method of moments is a method of estimation of population parameters. The same principle is used to derive higher moments like skewness…
- Stein's example In decision theory and estimation theory, Stein's example (also known as Stein's phenomenon or Stein's paradox) is the observation that when three or more…
- Nonparametric statistics Nonparametric statistics is a type of statistical analysis that makes minimal assumptions about the underlying distribution of the data being studied.…