Probability theory and stochastic processes Definition
Probability mass function
Builds on Discrete random variableRandom variable
Definition
Let be a discrete random variable on a probability space . The probability mass function of is the function with More generally, a probability mass function on a countable set is a function with .
Remarks
The set is countable, and . For each Borel set , . For a fair die, for and for other .
Reading path
To understand this page from the ground up, read these 42 pages in order. The foundations come first.
- Construction of the reals from Cauchy sequences concept
- Element definition
- Integers object
- Ordered field definition
- Proposition concept
- Random experiment concept
- Rational numbers object
- Real numbers object
- Set definition
- Ring of integers statement
- Disjunction definition
- Implication definition
- Predicate definition
- Ordered pair definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Cartesian product definition
- Subset definition
- The rationals form an ordered field statement
- Uniqueness quantifier definition
- Binary relation definition
- Universal set definition
- Order on the reals definition
- Power set definition
- Complement definition
- Function definition
- Interval definition
- Injective function definition
- Preimage of a set definition
- Sigma-algebra definition
- Countable set definition
- Event definition
- Borel sigma-algebra definition
- Probability axioms concept
- Probability measure definition
- Probability space definition
- Random variable definition
- Discrete random variable definition
- Probability mass function definition
Where this leads
92 pages build on this one.
- Chernoff bound
- Law of the unconscious statistician
- Characteristic function of a sum of independent random variables
- Bernoulli process
- Likelihood function
- Poisson point process
- De Moivre–Laplace theorem
- Convolution of probability distributions
- Mean of the Poisson distribution
- Method of moments
- Moment-generating function of the normal distribution
- Kurtosis
- Mean of the geometric distribution
- Neyman–Pearson lemma
- Central limit theorem
- Lévy's continuity theorem
- Maximum likelihood estimation
- Skewness
- Galton–Watson process
- Bernoulli distribution
- Bayesian inference
- Discrete uniform distribution
- Coupon collector's problem
- Characteristic function
- Moment-generating function
- Characteristic function of the normal distribution
- Sum of independent normal random variables
- Moment
- Expectation with respect to the binomial distribution
- Cumulant generating function
- Generating function of a sum of independent random variables
- Hypergeometric distribution
- Moments are derivatives of the moment-generating function at zero
- The characteristic function determines the distribution
- Poisson distribution
- Binomial distribution
- Hoeffding's inequality
- Moment-generating function of a sum of independent random variables
- Geometric distribution
- Poisson limit theorem
- Negative binomial distribution
- Sum of independent Poisson random variables
- Conditional probability distribution
- Probability-generating function
- Memorylessness
- Central moment
- Poisson regression
- Koksma–Hlawka inequality
- Hodges' superefficient estimator
- Cramér–Wold theorem
- Boolean model
- Wald–Wolfowitz optimality of the sequential probability ratio test
- Consistency of the maximum likelihood estimator
- Bayes factor
- Lindley's paradox
- M-estimator
- McDiarmid's inequality
- Asymptotic normality of the maximum likelihood estimator
- Score
- Edgeworth expansion
- Monotone likelihood ratio
- Wilcoxon signed-rank test
- Whittle likelihood
- Logistic regression
- Azuma's inequality
- Erdős–Kac theorem
- Monte Carlo integration
- Delta method
- Noncentral chi-squared distribution
- Hájek–Le Cam convolution theorem
- Minimum-variance unbiased estimator
- Sign test
- Empirical likelihood
- Bayesian information criterion
- Berry–Esseen theorem
- Akaike information criterion
- Credible interval
- Estimating equations
- Generalized method of moments
- Bernstein inequalities
- Missing data mechanisms
- Likelihood-ratio test
- Conjugate prior
- Expectation–maximization algorithm
- Wald test
- Generalized linear model
- Box–Jenkins method
- Binomial proportion confidence interval
- Fisher's exact test
- Likelihood principle
- Observed information
- Point estimation
Further reading
- Web https://en.wikipedia.org/wiki/Probability_mass_function, Formal definition
About this page
| Tag | 0WF4EJP91W |
|---|---|
| URI | m2://0WF4EJP91W |
| Kind | definition |
| Writing | W0 stub |
| MSC | 60E05 |
| Defines | Probability mass function |
| Uses | Discrete random variable, Random variable |
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What links here
Used by
- Law of the unconscious statistician
- Likelihood function
- Convolution of probability distributions
- Bernoulli distribution
- Discrete uniform distribution
- Hypergeometric distribution
- Poisson distribution
- Binomial distribution
- Geometric distribution
- Negative binomial distribution
- Conditional probability distribution
- Probability-generating function