Catalog of articles in probability theory

Probability
Outline Catalog of articles Probabilists Glossary Notation Journals Category
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This page lists articles related to probability theory. In particular, it lists many articles corresponding to specific probability distributions. Such articles are marked here by a code of the form (X:Y), which refers to number of random variables involved and the type of the distribution. For example (2:DC) indicates a distribution with two random variables, discrete or continuous. Other codes are just abbreviations for topics. The list of codes can be found in the table of contents.

Core probability: selected topics

Probability theory

Basic notions (bsc)

• Random variable
• Continuous probability distribution / (1:C)
• Cumulative distribution function / (1:DCR)
• Discrete probability distribution / (1:D)
• Independent and identically-distributed random variables / (FS:BDCR)
• Joint probability distribution / (F:DC)
• Marginal distribution / (2F:DC)
• Probability density function / (1:C)
• Probability distribution / (1:DCRG)
• Probability distribution function
• Probability mass function / (1:D)
• Sample space

Instructive examples (paradoxes) (iex)

• Berkson's paradox / (2:B)
• Bertrand's box paradox / (F:B)
• Borel–Kolmogorov paradox / cnd (2:CM)
• Boy or Girl paradox / (2:B)
• Exchange paradox / (2:D)
• Intransitive dice
• Monty Hall problem / (F:B)
• Necktie paradox
• Simpson's paradox
• Sleeping Beauty problem
• St. Petersburg paradox / mnt (1:D)
• Three Prisoners problem
• Two envelopes problem

Moments (mnt)

• Expected value / (12:DCR)
• Canonical correlation / (F:R)
• Carleman's condition / anl (1:R)
• Central moment / (1:R)
• Coefficient of variation / (1:R)
• Correlation / (2:R)
• Correlation function / (U:R)
• Covariance / (2F:R) (1:G)
• Covariance function / (U:R)
• Covariance matrix / (F:R)
• Cumulant / (12F:DCR)
• Factorial moment / (1:R)
• Factorial moment generating function / anl (1:R)
• Fano factor
• Geometric standard deviation / (1:R)
• Hamburger moment problem / anl (1:R)
• Hausdorff moment problem / anl (1:R)
• Isserlis Gaussian moment theorem / Gau
• Jensen's inequality / (1:DCR)
• Kurtosis / (1:CR)
• Law of the unconscious statistician / (1:DCR)
• Moment / (12FU:CRG)
• Law of total covariance / (F:R)
• Law of total cumulance / (F:R)
• Law of total expectation / (F:DR)
• Law of total variance / (F:R)
• Logmoment generating function
• Marcinkiewicz–Zygmund inequality / inq
• Method of moments / lmt (L:R)
• Moment problem / anl (1:R)
• Moment-generating function / anl (1F:R)
• Second moment method / (1FL:DR)
• Skewness / (1:R)
• St. Petersburg paradox / iex (1:D)
• Standard deviation / (1:DCR)
• Standardized moment / (1:R)
• Stieltjes moment problem / anl (1:R)
• Trigonometric moment problem / anl (1:R)
• Uncorrelated / (2:R)
• Variance / (12F:DCR)
• Variance-to-mean ratio / (1:R)

Inequalities (inq)

• Chebyshev's inequality / (1:R)
• An inequality on location and scale parameters / (1:R)
• Azuma's inequality / (F:BR)
• Bennett's inequality / (F:R)
• Bernstein inequalities / (F:R)
• Bhatia–Davis inequality
• Chernoff bound / (F:B)
• Doob's martingale inequality / (FU:R)
• Dudley's theorem / Gau
• Entropy power inequality
• Etemadi's inequality / (F:R)
• Gauss's inequality
• Hoeffding's inequality / (F:R)
• Khintchine inequality / (F:B)
• Kolmogorov's inequality / (F:R)
• Marcinkiewicz–Zygmund inequality / mnt
• Markov's inequality / (1:R)
• McDiarmid's inequality
• Multidimensional Chebyshev's inequality
• Paley–Zygmund inequality / (1:R)
• Pinsker's inequality / (2:R)
• Vysochanskiï–Petunin inequality / (1:C)

Markov chains, processes, fields, networks (Mar)

• Markov chain / (FLSU:D)
• Additive Markov chain
• Bayesian network / Bay
• Birth–death process / (U:D)
• CIR process / scl
• Chapman–Kolmogorov equation / (F:DC)
• Cheeger bound / (L:D)
• Conductance
• Contact process
• Continuous-time Markov process / (U:D)
• Detailed balance / (F:D)
• Examples of Markov chains / (FL:D)
• Feller process / (U:G)
• Fokker–Planck equation / scl anl
• Foster's theorem / (L:D)
• Gauss–Markov process / Gau
• Geometric Brownian motion / scl
• Hammersley–Clifford theorem / (F:C)
• Harris chain / (L:DC)
• Hidden Markov model / (F:D)
• Hidden Markov random field
• Hunt process / (U:R)
• Kalman filter / (F:C)
• Kolmogorov backward equation / scl
• Kolmogorov's criterion / (F:D)
• Kolmogorov’s generalized criterion / (U:D)
• Krylov–Bogolyubov theorem / anl
• Lumpability
• Markov additive process
• Markov blanket / Bay
• Markov chain mixing time / (L:D)
• Markov decision process
• Markov information source
• Markov kernel
• Markov logic network
• Markov network
• Markov process / (U:D)
• Markov property / (F:D)
• Markov random field
• Master equation / phs (U:D)
• Milstein method / scl
• Moran process
• Ornstein–Uhlenbeck process / Gau scl
• Partially observable Markov decision process
• Product-form solution / spr
• Quantum Markov chain / phs
• Semi-Markov process
• Stochastic matrix / anl
• Telegraph process / (U:B)
• Variable-order Markov model
• Wiener process / Gau scl

Gaussian random variables, vectors, functions (Gau)

• Normal distribution / spd
• Abstract Wiener space
• Brownian bridge
• Classical Wiener space
• Concentration dimension
• Dudley's theorem / inq
• Estimation of covariance matrices
• Fractional Brownian motion
• Gaussian isoperimetric inequality
• Gaussian measure / anl
• Gaussian random field
• Gauss–Markov process / Mar
• Integration of the normal density function / spd anl
• Gaussian process
• Isserlis Gaussian moment theorem / mnt
• Karhunen–Loève theorem
• Large deviations of Gaussian random functions / lrd
• Lévy's modulus of continuity theorem / (U:R)
• Matrix normal distribution / spd
• Multivariate normal distribution / spd
• Ornstein–Uhlenbeck process / Mar scl
• Paley–Wiener integral / anl
• Pregaussian class
• Schilder's theorem / lrd
• Wiener process / Mar scl

Conditioning (cnd)

• Conditioning / (2:BDCR)
• Bayes' theorem / (2:BCG)
• Borel–Kolmogorov paradox / iex (2:CM)
• Conditional expectation / (2:BDR)
• Conditional independence / (3F:BR)
• Conditional probability
• Conditional probability distribution / (2:DC)
• Conditional random field / (F:R)
• Disintegration theorem / anl (2:G)
• Inverse probability / Bay
• Luce's choice axiom
• Regular conditional probability / (2:G)
• Rule of succession / (F:B)

Specific distributions (spd)

• Binomial distribution / (1:D)
• (a,b,0) class of distributions / (1:D)
• Anscombe transform
• Bernoulli distribution / (1:B)
• Beta distribution / (1:C)
• Bose–Einstein statistics / (F:D)
• Cantor distribution / (1:C)
• Cauchy distribution / (1:C)
• Chi-squared distribution / (1:C)
• Compound Poisson distribution / (F:DR)
• Degenerate distribution / (1:D)
• Dirichlet distribution / (F:C)
• Discrete phase-type distribution / (1:D)
• Erlang distribution / (1:C)
• Exponential-logarithmic distribution / (1:C)
• Exponential distribution / (1:C)
• F-distribution / (1:C)
• Fermi–Dirac statistics / (1F:D)
• Fisher–Tippett distribution / (1:C)
• Gamma distribution / (1:C)
• Generalized normal distribution / (1:C)
• Geometric distribution / (1:D)
• Half circle distribution / (1:C)
• Hypergeometric distribution / (1:D)
• Normal distribution / Gau
• Integration of the normal density function / Gau anl
• Lévy distribution / (1:C)
• Matrix normal distribution / Gau
• Maxwell–Boltzmann statistics / (F:D)
• McCullagh's parametrization of the Cauchy distributions / (1:C)
• Multinomial distribution / (F:D)
• Multivariate normal distribution / Gau
• Negative binomial distribution / (1:D)
• Pareto distribution / (1:C)
• Phase-type distribution / (1:C)
• Poisson distribution / (1:D)
• Power law / (1:C)
• Skew normal distribution / (1:C)
• Stable distribution / (1:C)
• Student's t-distribution / (1:C)
• Tracy–Widom distribution / rmt
• Triangular distribution / (1:C)
• Weibull distribution / (1:C)
• Wigner semicircle distribution / (1:C)
• Wishart distribution / (F:C)
• Zeta distribution / (1:D)
• Zipf's law / (1:D)

Empirical measure (emm)

• Donsker's theorem / (LU:C)
• Empirical distribution function
• Empirical measure / (FL:RG) (U:D)
• Empirical process / (FL:RG) (U:D)
• Glivenko–Cantelli theorem / (FL:RG) (U:D)
• Khmaladze transformation / (FL:RG) (U:D)
• Vapnik–Chervonenkis theory

Limit theorems (lmt)

• Central limit theorem / (L:R)
• Berry–Esseen theorem / (F:R)
• Characteristic function / anl (1F:DCR)
• De Moivre–Laplace theorem / (L:BD)
• Helly–Bray theorem / anl (L:R)
• Illustration of the central limit theorem / (L:DC)
• Lindeberg's condition
• Lyapunov's central limit theorem / (L:R)
• Lévy's continuity theorem / anl (L:R)
• Lévy's convergence theorem / (S:R)
• Martingale central limit theorem / (S:R)
• Method of moments / mnt (L:R)
• Slutsky's theorem / anl
• Weak convergence of measures / anl

Large deviations (lrd)

• Large deviations theory
• Contraction principle
• Cramér's theorem
• Exponentially equivalent measures
• Freidlin–Wentzell theorem
• Laplace principle
• Large deviations of Gaussian random functions / Gau
• Rate function
• Schilder's theorem / Gau
• Tilted large deviation principle
• Varadhan's lemma

Random graphs (rgr)

• Random graph
• BA model
• Barabási–Albert model
• Erdős–Rényi model
• Percolation theory / phs (L:B)
• Percolation threshold / phs
• Random geometric graph
• Random regular graph
• Watts and Strogatz model

Random matrices (rmt)

• Random matrix
• Circular ensemble
• Gaussian matrix ensemble
• Tracy–Widom distribution / spd
• Weingarten function / anl

Stochastic calculus (scl)

• Itô calculus
• Bessel process
• CIR process / Mar
• Doléans-Dade exponential
• Dynkin's formula
• Euler–Maruyama method
• Feynman–Kac formula
• Filtering problem
• Fokker–Planck equation / Mar anl
• Geometric Brownian motion / Mar
• Girsanov theorem
• Green measure
• Heston model / fnc
• Hörmander's condition / anl
• Infinitesimal generator
• Itô's lemma
• Itô calculus
• Itô diffusion
• Itô isometry
• Itô's lemma
• Kolmogorov backward equation / Mar
• Local time
• Milstein method / Mar
• Novikov's condition
• Ornstein–Uhlenbeck process / Gau Mar
• Quadratic variation
• Random dynamical system / rds
• Reversible diffusion
• Runge–Kutta method
• Russo–Vallois integral
• Schramm–Loewner evolution
• Semimartingale
• Stochastic calculus
• Stochastic differential equation
• Stochastic processes and boundary value problems / anl
• Stratonovich integral
• Tanaka equation
• Tanaka's formula
• Wiener process / Gau Mar
• Wiener sausage

Malliavin calculus (Mal)

• Malliavin calculus
• Clark–Ocone theorem
• H-derivative
• Integral representation theorem for classical Wiener space
• Integration by parts operator
• Malliavin derivative
• Malliavin's absolute continuity lemma
• Ornstein–Uhlenbeck operator
• Skorokhod integral

Random dynamical systems (rds)

Random dynamical system / scl

• Absorbing set
• Base flow
• Pullback attractor

Analytic aspects (including measure theoretic) (anl)

• Probability space
• Carleman's condition / mnt (1:R)
• Characteristic function / lmt (1F:DCR)
• Contiguity#Probability theory
• Càdlàg
• Disintegration theorem / cnd (2:G)
• Dynkin system
• Exponential family
• Factorial moment generating function / mnt (1:R)
• Filtration
• Fokker–Planck equation / scl Mar
• Gaussian measure / Gau
• Hamburger moment problem / mnt (1:R)
• Hausdorff moment problem / mnt (1:R)
• Helly–Bray theorem / lmt (L:R)
• Hörmander's condition / scl
• Integration of the normal density function / spd Gau
• Kolmogorov extension theorem / (SU:R)
• Krylov–Bogolyubov theorem / Mar
• Law (stochastic processes) / (U:G)
• Location-scale family
• Lévy's continuity theorem / lmt (L:R)
• Minlos' theorem
• Moment problem / mnt (1:R)
• Moment-generating function / mnt (1F:R)
• Natural filtration / (U:G)
• Paley–Wiener integral / Gau
• Sazonov's theorem
• Slutsky's theorem / lmt
• Standard probability space
• Stieltjes moment problem / mnt (1:R)
• Stochastic matrix / Mar
• Stochastic processes and boundary value problems / scl
• Trigonometric moment problem / mnt (1:R)
• Weak convergence of measures / lmt
• Weingarten function / rmt

Core probability: other articles, by number and type of random variables

A single random variable (1:)

Binary (1:B)

• Bernoulli trial / (1:B)
• Complementary event / (1:B)
• Entropy / (1:BDC)
• Event / (1:B)
• Indecomposable distribution / (1:BDCR)
• Indicator function / (1F:B)

Discrete (1:D)

• Binomial probability / (1:D)
• Continuity correction / (1:DC)
• Entropy / (1:BDC)
• Equiprobable / (1:D)
• Hann function / (1:D)
• Indecomposable distribution / (1:BDCR)
• Infinite divisibility / (1:DCR)
• Le Cam's theorem / (F:B) (1:D)
• Limiting density of discrete points / (1:DC)
• Mean difference / (1:DCR)
• Memorylessness / (1:DCR)
• Probability vector / (1:D)
• Probability-generating function / (1:D)
• Tsallis entropy / (1:DC)

Continuous (1:C)

• Almost surely / (1:C) (LS:D)
• Continuity correction / (1:DC)
• Edgeworth series / (1:C)
• Entropy / (1:BDC)
• Indecomposable distribution / (1:BDCR)
• Infinite divisibility / (1:DCR)
• Limiting density of discrete points / (1:DC)
• Location parameter / (1:C)
• Mean difference / (1:DCR)
• Memorylessness / (1:DCR)
• Monotone likelihood ratio / (1:C)
• Scale parameter / (1:C)
• Stability / (1:C)
• Stein's lemma / (12:C)
• Truncated distribution / (1:C)
• Tsallis entropy / (1:DC)

Real-valued, arbitrary (1:R)

• Heavy-tailed distribution / (1:R)
• Indecomposable distribution / (1:BDCR)
• Infinite divisibility / (1:DCR)
• Locality / (1:R)
• Mean difference / (1:DCR)
• Memorylessness / (1:DCR)
• Quantile / (1:R)
• Survival function / (1:R)
• Taylor expansions for the moments of functions of random variables / (1:R)

Random point of a manifold (1:M)

• Bertrand's paradox / (1:M)

General (random element of an abstract space) (1:G)

• Pitman–Yor process / (1:G)
• Random compact set / (1:G)
• Random element / (1:G)

Two random variables (2:)

Binary (2:B)

• Coupling / (2:BRG)
• Craps principle / (2:B)

Discrete (2:D)

• Kullback–Leibler divergence / (2:DCR)
• Mutual information / (23F:DC)

Continuous (2:C)

• Copula / (2F:C)
• Cramér's theorem / (2:C)
• Kullback–Leibler divergence / (2:DCR)
• Mutual information / (23F:DC)
• Normally distributed and uncorrelated does not imply independent / (2:C)
• Posterior probability / Bay (2:C)
• Stein's lemma / (12:C)

Real-valued, arbitrary (2:R)

• Coupling / (2:BRG)
• Hellinger distance / (2:R)
• Kullback–Leibler divergence / (2:DCR)
• Lévy metric / (2:R)
• Total variation / (2:R)

General (random element of an abstract space) (2:G)

• Coupling / (2:BRG)
• Lévy–Prokhorov metric / (2:G)
• Wasserstein metric / (2:G)

Three random variables (3:)

Binary (3:B)

• Pairwise independence / (3:B) (F:R)

Discrete (3:D)

• Mutual information / (23F:DC)

Continuous (3:C)

• Mutual information / (23F:DC)

Finitely many random variables (F:)

Binary (F:B)

• Bertrand's ballot theorem / (F:B)
• Boole's inequality / (FS:B)
• Coin flipping / (F:B)
• Collectively exhaustive events / (F:B)
• Inclusion–exclusion principle / (F:B)
• Independence / (F:BR)
• Indicator function / (1F:B)
• Law of total probability / (F:B)
• Le Cam's theorem / (F:B) (1:D)
• Leftover hash lemma / (F:B)
• Lovász local lemma / (F:B)
• Mutually exclusive / (F:B)
• Random walk / (FLS:BD) (U:C)
• Schuette–Nesbitt formula / (F:B)

Discrete (F:D)

• Coupon collector's problem / gmb (F:D)
• Graphical model / (F:D)
• Kirkwood approximation / (F:D)
• Mutual information / (23F:DC)
• Random field / (F:D)
• Random walk / (FLS:BD) (U:C)
• Stopped process / (FU:DG)

Continuous (F:C)

• Anderson's theorem / (F:C)
• Autoregressive integrated moving average / (FS:C)
• Autoregressive model / (FS:C)
• Autoregressive moving average model / (FS:C)
• Copula / (2F:C)
• Maxwell's theorem / (F:C)
• Moving average model / (FS:C)
• Mutual information / (23F:DC)
• Schrödinger method / (F:C)

Real-valued, arbitrary (F:R)

• Bapat–Beg theorem / (F:R)
• Comonotonicity / (F:R)
• Doob martingale / (F:R)
• Independence / (F:BR)
• Littlewood–Offord problem / (F:R)
• Lévy flight / (F:R) (U:C)
• Martingale / (FU:R)
• Martingale difference sequence / (F:R)
• Maximum likelihood / (FL:R)
• Multivariate random variable / (F:R)
• Optional stopping theorem / (FS:R)
• Pairwise independence / (3:B) (F:R)
• Stopping time / (FU:R)
• Time series / (FS:R)
• Wald's equation / (FS:R)
• Wick product / (F:R)

General (random element of an abstract space) (F:G)

• Finite-dimensional distribution / (FU:G)
• Hitting time / (FU:G)
• Stopped process / (FU:DG)

A large number of random variables (finite but tending to infinity) (L:)

Binary (L:B)

• Random walk / (FLS:BD) (U:C)

Discrete (L:D)

• Almost surely / (1:C) (LS:D)
• Gambler's ruin / gmb (L:D)
• Loop-erased random walk / (L:D) (U:C)
• Preferential attachment / (L:D)
• Random walk / (FLS:BD) (U:C)
• Typical set / (L:D)

Real-valued, arbitrary (L:R)

• Convergence of random variables / (LS:R)
• Law of large numbers / (LS:R)
• Maximum likelihood / (FL:R)
• Stochastic convergence / (LS:R)

An infinite sequence of random variables (S:)

Binary (S:B)

• Bernoulli process / (S:B)
• Boole's inequality / (FS:B)
• Borel–Cantelli lemma / (S:B)
• De Finetti's theorem / (S:B)
• Exchangeable random variables / (S:BR)
• Random walk / (FLS:BD) (U:C)

Discrete (S:D)

• Almost surely / (1:C) (LS:D)
• Asymptotic equipartition property / (S:DC)
• Bernoulli scheme / (S:D)
• Branching process / (S:D)
• Chinese restaurant process / (S:D)
• Galton–Watson process / (S:D)
• Information source / (S:D)
• Random walk / (FLS:BD) (U:C)

Continuous (S:C)

• Asymptotic equipartition property / (S:DC)
• Autoregressive integrated moving average / (FS:C)
• Autoregressive model / (FS:C)
• Autoregressive–moving-average model / (FS:C)
• Moving-average model / (FS:C)

Real-valued, arbitrary (S:R)

• Big O in probability notation / (S:R)
• Convergence of random variables / (LS:R)
• Doob's martingale convergence theorems / (SU:R)
• Ergodic theory / (S:R)
• Exchangeable random variables / (S:BR)
• Hewitt–Savage zero–one law / (S:RG)
• Kolmogorov's zero–one law / (S:R)
• Law of large numbers / (LS:R)
• Law of the iterated logarithm / (S:R)
• Maximal ergodic theorem / (S:R)
• Op (statistics) / (S:R)
• Optional stopping theorem / (FS:R)
• Stationary process / (SU:R)
• Stochastic convergence / (LS:R)
• Stochastic process / (SU:RG)
• Time series / (FS:R)
• Uniform integrability / (S:R)
• Wald's equation / (FS:R)

General (random element of an abstract space) (S:G)

• Hewitt–Savage zero–one law / (S:RG)
• Mixing / (S:G)
• Skorokhod's representation theorem / (S:G)
• Stochastic process / (SU:RG)

Uncountably many random variables (continuous-time processes etc) (U:)

Discrete (U:D)

• Counting process / (U:D)
• Cox process / (U:D)
• Dirichlet process / (U:D)
• Lévy process / (U:DC)
• Non-homogeneous Poisson process / (U:D)
• Point process / (U:D)
• Poisson process / (U:D)
• Poisson random measure / (U:D)
• Random measure / (U:D)
• Renewal theory / (U:D)
• Stopped process / (FU:DG)

Continuous (U:C)

• Brownian motion / phs (U:C)
• Gamma process / (U:C)
• Loop-erased random walk / (L:D) (U:C)
• Lévy flight / (F:R) (U:C)
• Lévy process / (U:DC)
• Martingale representation theorem / (U:C)
• Random walk / (FLS:BD) (U:C)
• Skorokhod's embedding theorem / (U:C)

Real-valued, arbitrary (U:R)

• Compound Poisson process / (U:R)
• Continuous stochastic process / (U:RG)
• Doob's martingale convergence theorems / (SU:R)
• Doob–Meyer decomposition theorem / (U:R)
• Feller-continuous process / (U:R)
• Kolmogorov continuity theorem / (U:R)
• Local martingale / (U:R)
• Martingale / (FU:R)
• Stationary process / (SU:R)
• Stochastic process / (SU:RG)
• Stopping time / (FU:R)

General (random element of an abstract space) (U:G)

• Adapted process / (U:G)
• Continuous stochastic process / (U:RG)
• Finite-dimensional distribution / (FU:G)
• Hitting time / (FU:G)
• Killed process / (U:G)
• Progressively measurable process / (U:G)
• Sample-continuous process / (U:G)
• Stochastic process / (SU:RG)
• Stopped process / (FU:DG)

Around the core

General aspects (grl)

• Aleatoric
• Average
• Bean machine
• Cox's theorem
• Equipossible
• Exotic probability
• Extractor
• Free probability
• Frequency
• Frequency probability
• Impossible event
• Infinite monkey theorem
• Information geometry
• Law of Truly Large Numbers
• Littlewood's law
• Observational error
• Principle of indifference
• Principle of maximum entropy
• Probability
• Probability interpretations
• Propensity probability
• Random number generator
• Random sequence
• Randomization
• Randomness
• Statistical dispersion
• Statistical regularity
• Uncertainty
• Upper and lower probabilities
• Urn problem

Foundations of probability theory (fnd)

• Algebra of random variables
• Belief propagation
• Dempster–Shafer theory
• Dutch book
• Elementary event
• Normalizing constant
• Possibility theory
• Probability axioms
• Transferable belief model
• Unit measure

Gambling (gmb)

• Betting
• Bookmaker
• Coherence
• Coupon collector's problem / (F:D)
• Coupon collector's problem (generating function approach) / (F:D)
• Gambler's fallacy
• Gambler's ruin / (L:D)
• Game of chance
• Inverse gambler's fallacy
• Lottery
• Lottery machine
• Luck
• Martingale
• Odds
• Pachinko
• Parimutuel betting
• Parrondo's paradox
• Pascal's wager
• Poker probability
• Poker probability (Omaha)
• Poker probability (Texas hold 'em)
• Pot odds
• Proebsting's paradox
• Roulette
• Spread betting
• The man who broke the bank at Monte Carlo

Coincidence (cnc)

• Bible code
• Birthday paradox
• Birthday problem
• Index of coincidence
• Spurious relationship

Algorithmics (alg)

• Algorithmic Lovász local lemma
• Box–Muller transform
• Gibbs sampling
• Inverse transform sampling method
• Las Vegas algorithm
• Metropolis algorithm
• Monte Carlo method
• Panjer recursion
• Probabilistic Turing machine
• Probabilistic algorithm
• Probabilistically checkable proof
• Probable prime
• Stochastic programming

Bayesian approach (Bay)

• Bayes factor
• Bayesian model comparison
• Bayesian network / Mar
• Bayesian probability
• Bayesian programming
• Bayesianism
• Checking if a coin is fair
• Conjugate prior
• Factor graph
• Good–Turing frequency estimation
• Imprecise probability
• Inverse probability / cnd
• Marginal likelihood
• Markov blanket / Mar
• Posterior probability / (2:C)
• Prior probability
• SIPTA
• Subjective logic
• Subjectivism / hst

Financial mathematics (fnc)

• Allais paradox
• Black–Scholes
• Cox–Ingersoll–Ross model
• Forward measure
• Heston model / scl
• Jump process
• Jump-diffusion model
• Kelly criterion
• Market risk
• Mathematics of bookmaking
• Risk
• Risk-neutral measure
• Ruin theory
• Sethi model
• Technical analysis
• Value at risk
• Variance gamma process / spr
• Vasicek model
• Volatility

Physics (phs)

• Boltzmann factor
• Brownian motion / (U:C)
• Brownian ratchet
• Cosmic variance
• Critical phenomena
• Diffusion-limited aggregation
• Fluctuation theorem
• Gibbs state
• Information entropy
• Lattice model
• Master equation / Mar (U:D)
• Negative probability
• Nonextensive entropy
• Partition function
• Percolation theory / rgr (L:B)
• Percolation threshold / rgr
• Probability amplitude
• Quantum Markov chain / Mar
• Quantum probability
• Scaling limit
• Statistical mechanics
• Statistical physics
• Vacuum expectation value

Genetics (gnt)

• Ewens's sampling formula
• Hardy–Weinberg principle
• Population genetics
• Punnett square
• Ronald Fisher

Stochastic process (spr)

• Anomaly time series
• Arrival theorem
• Beverton–Holt model
• Burke's theorem
• Buzen's algorithm
• Disorder problem
• Erlang unit
• G-network
• Gordon–Newell theorem
• Innovation
• Interacting particle system
• Jump diffusion
• M/M/1 model
• M/M/c model
• Mark V Shaney
• Markov chain Monte Carlo
• Markov switching multifractal
• Oscillator linewidth
• Poisson hidden Markov model
• Population process
• Probabilistic cellular automata
• Product-form solution / Mar
• Quasireversibility
• Queueing theory
• Recurrence period density entropy
• Variance gamma process / fnc
• Wiener equation

Geometric probability (geo)

• Boolean model
• Buffon's needle
• Geometric probability
• Hadwiger's theorem
• Integral geometry
• Random coil
• Stochastic geometry
• Vitale's random Brunn–Minkowski inequality

Empirical findings (emp)

• Benford's law
• Pareto principle

Historical (hst)

• History of probability
• Newton–Pepys problem
• Problem of points
• Subjectivism / Bay
• Sunrise problem
• The Doctrine of Chances

Miscellany (msc)

• B-convex space
• Conditional event algebra
• Error function
• Goodman–Nguyen–van Fraassen algebra
• List of mathematical probabilists
• Nuisance variable
• Probabilistic encryption
• Probabilistic logic
• Probabilistic proofs of non-probabilistic theorems
• Pseudocount

Counters of articles

• "Core": 455 (570)
• "Around": 198 (200)
• "Core selected": 311 (358)
• "Core others": 144 (212)

Here k(n) means: n links to k articles. (Some articles are linked more than once.)

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