discreteRV: Create and Manipulate Discrete Random Variables
Create, manipulate, transform, and simulate from discrete random variables. The syntax is modeled after that which is used in mathematical statistics and probability courses, but with powerful support for more advanced probability calculations. This includes the creation of joint random variables, and the derivation and manipulation of their conditional and marginal distributions.
- Andreas Buja [aut], Eric Hare [aut, cre], Heike Hofmann [aut]
- Date of publication
- 2015-09-16 10:05:21
- Eric Hare <email@example.com>
- Turn a probability vector with possible outcome values in the...
- Expected value of a random variable
- Compute the logical AND of two events
- Generic method for in operator function
- Compute the logical OR of two events
- Probability mass function of X^n
- Tests whether the random variables X and Y are independent
- Joint probability mass function of random variables X and Y
- Make a joint random variable consisting
- Kurtosis of a random variable
- Marginal distribution of a joint random variable
- Marginal distributions of a joint random variable
- Outcomes of random variable X
- Calculate probabilities of events
- Plot a random variable of class "RV"
- Plot a simulated random vector
- Print a random variable of class "RV"
- Probability mass function of random variable X
- Proportion of an event observed in a vector of simulated...
- Proportions of observed outcomes in one or more vectors of...
- Normal quantile plot for RVs to answer the question how close...
- Simulate n independent trials from a random variable X:
- Make a random variable consisting of possible outcome values...
- Standard deviation of a random variable
- Skewness of a random variable
- Skew of the empirical distribution of simulated data
- Sum of independent random variables
- Sum of independent identically distributed random variables
- Variance of a random variable
Files in this package