Category:Computational statistics

A

• Algorithmic inference‎ (4 P)
• Statistical algorithms‎ (2 C, 28 P)
• Artificial neural networks‎ (4 C, 154 P)

D

• Data mining‎ (9 C, 68 P)

J

• Computational statistics journals‎ (9 P)

M

• Markov chain Monte Carlo‎ (14 P)
• Monte Carlo methods‎ (7 C, 66 P)

N

• Non-uniform random numbers‎ (11 P)

S

• Statistical databases‎ (1 C, 4 P)
• Statistical software‎ (9 C, 56 P)

V

• Variance reduction‎ (8 P)

• Computational statistics

A

• Antithetic variates
• Types of artificial neural networks
• Artificial precision
• ArviZ
• Auxiliary particle filter

B

• Bayesian inference using Gibbs sampling
• Bootstrap aggregating
• Bootstrap error-adjusted single-sample technique
• Bootstrapping (statistics)
• Bootstrapping populations
• Iain Buchan

C

• Conformal prediction
• Continuity correction
• Control variates

F

• FastICA

G

• Gaussian process approximations
• Group method of data handling
• Guess value

H

• History of artificial neural networks

I

• Integrated nested Laplace approximations
• Isomap
• Iterated conditional modes

J

• Jackknife resampling
• Joint Approximation Diagonalization of Eigen-matrices

L

• Linear least squares

M

• Markov chain Monte Carlo
• Mathematics of artificial neural networks
• Multivariate kernel density estimation

N

• Neural network (machine learning)

O

• Out-of-bag error
• Owen's T function

P

• Particle filter
• Plug-in principle
• ProbLog
• Projection filters
• PyMC

R

• Radial basis function network
• Random forest
• Reversible-jump Markov chain Monte Carlo

S

• Semidefinite embedding
• Signal magnitude area
• Spiking neural network
• Stan (software)
• Statistical relational learning
• Stochastic gradient descent
• Stochastic gradient Langevin dynamics
• Symbolic data analysis
• Synthetic measure

T

• Twisting properties

V

• Vecchia approximation

Y

• Yates's correction for continuity