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.

AuthorAndreas Buja [aut], Eric Hare [aut, cre], Heike Hofmann [aut]
Date of publication2015-09-16 10:05:21
MaintainerEric Hare <erichare@iastate.edu>
LicenseGPL-3
Version1.2.2
https://github.com/erichare/discreteRV

View on CRAN

Man pages

as.RV: Turn a probability vector with possible outcome values in the...

E: Expected value of a random variable

grapes-AND-grapes: Compute the logical AND of two events

grapes-in-grapes: Generic method for in operator function

grapes-OR-grapes: Compute the logical OR of two events

iid: Probability mass function of X^n

independent: Tests whether the random variables X and Y are independent

joint: Joint probability mass function of random variables X and Y

jointRV: Make a joint random variable consisting

KURT: Kurtosis of a random variable

marginal: Marginal distribution of a joint random variable

margins: Marginal distributions of a joint random variable

outcomes: Outcomes of random variable X

P: Calculate probabilities of events

plot.RV: Plot a random variable of class "RV"

plot.RVsim: Plot a simulated random vector

print.RV: Print a random variable of class "RV"

probs: Probability mass function of random variable X

Prop: Proportion of an event observed in a vector of simulated...

props: Proportions of observed outcomes in one or more vectors of...

qqnorm.RV: Normal quantile plot for RVs to answer the question how close...

rsim: Simulate n independent trials from a random variable X:

RV: Make a random variable consisting of possible outcome values...

SD: Standard deviation of a random variable

SKEW: Skewness of a random variable

skewSim: Skew of the empirical distribution of simulated data

SofI: Sum of independent random variables

SofIID: Sum of independent identically distributed random variables

V: Variance of a random variable

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.