Estimation theory

B

• Bayesian estimation (2 C, 17 P)

E

• Errors and residuals (9 P)
• Estimator (1 C, 30 P)

I

• Statistical intervals (10 P)

M

• Estimation methods (8 C, 42 P)

P

• Point estimation performance (13 P)

R

• Regression analysis (9 C, 94 P)

U

• U-statistics (1 P)

• Estimation theory

1

• 1.96

9

• 97.5th percentile point

A

• Average treatment effect

B

• Bayesian message classification

C

• CDF-based nonparametric confidence interval
• Chapman–Robbins bound
• Confidence and prediction bands
• Confidence distribution
• Confidence region
• Coverage probability
• Cramér–Rao bound

D

• Earth:Data assimilation

E

• Efficiency (statistics)
• Empirical probability
• Endogeneity (econometrics)
• Estimand
• Estimation
• Estimation statistics

F

• Fisher consistency
• Fisher information
• Formation matrix

G

• Gelman-Rubin statistic
• Generalized pencil-of-function method

I

• Identifiability

K

• Kullback's inequality

L

• Least-angle regression
• Lehmann–Scheffé theorem
• Likelihood principle
• Linear regression
• Location estimation in sensor networks

M

• Matrix regularization
• MINQUE

N

• Nuisance parameter

O

• Observed information

P

• Parameter identification problem
• Parameter space
• Point estimation

R

• Rao–Blackwell theorem
• Relaxed intersection
• Richardson–Lucy deconvolution

S

• Set estimation
• Set identification
• Shrinkage (statistics)
• Statistical learning theory
• Stein's example
• Proof of Stein's example

V

• V-statistic

Z

• Ziv–Zakai bound