Category:Computational statistics

A

• ► Algorithmic inference‎ (4 P)
• ► Statistical algorithms‎ (2 C, 25 P)
• ► Artificial neural networks‎ (2 C, 155 P)

D

• ► Data mining‎ (9 C, 61 P)

J

• ► Computational statistics journals‎ (8 P)

M

• ► Markov chain Monte Carlo‎ (12 P)
• ► Monte Carlo methods‎ (7 C, 62 P)

N

• ► Non-uniform random numbers‎ (10 P)

S

• ► Statistical databases‎ (4 P)
• ► Statistical software‎ (9 C, 53 P)

V

• ► Variance reduction‎ (8 P)

• Computational statistics

A

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

B

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

C

• Continuity correction
• Control variates

F

• FastICA

G

• Group method of data handling
• Guess value

I

• Isomap
• Iterated conditional modes

J

• Jackknife resampling
• Joint Approximation Diagonalization of Eigen-matrices

L

• Linear least squares

M

• Markov chain Monte Carlo
• Multivariate kernel density estimation

N

• ND4J (software)
• ND4S

O

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

P

• Particle filter
• Plug-in principle
• PyMC3

R

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

S

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

T

• Twisting properties