Catalog Of Articles In Probability Theory

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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Original source: https://en.wikipedia.org/wiki/Catalog of articles in probability theory. Read more

Probability

Outline Catalog of articles Probabilists Glossary Notation Journals Category
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