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lestat (version 1.9)

A Package for Learning Statistics

Description

Some simple objects and functions to do statistics using linear models and a Bayesian framework.

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Version

Install

install.packages('lestat')

Monthly Downloads

203

Version

1.9

License

GPL-2

Maintainer

Petter Mostad

Last Published

June 12th, 2018

Functions in lestat (1.9)

mdiscretedistribution

Create Object Representing a Multivariate Discrete Distribution
fittedvalues

Compute Fitted Values for a Linear Model
normalexpgamma

A Normal-ExpGamma Distribution
invcdf

Compute the Inverse Cumulative Distribution Function
leastsquares

Find the Least Squares Solution in a Linear Model
gammadistribution

Create a Gamma Distribution
normal

A Normal Distribution
normalgamma

A Normal-Gamma Distribution
designOneGroup

Create a Design Matrix for One Group of Observations
posteriornormal1

Compute the Posterior Distribution for Parameters of One Normal Distribution
simulate.normal

Simulate values from a Probability Distribution
p.value

Compute the p-value for a Distribution
mnormalgamma

A Multivariate Normal-Gamma Distribution
marginal

A Marginal of a Multivariate Distribution
linearpredict

Create a Linear Extension of a Distribution
tdistribution

A t-distribution
mnormalexpgamma

A Multivariate Normal-ExpGamma Distribution
summary.normal

Summary of a Probability Distribution Object
uniformdistribution

A Uniform Distribution
variance

The Variance of a Distribution
lestat-package

LEarning STATistics using Bayesian object oriented computation
probability

The Probability at a Value for a Discrete Distribution
mnormal

A Multivariate Normal Distribution
muniformdistribution

A Multivariate Uniform Distribution
linearmodel

Compute the Posterior Distribution for a Linear Model
poissondistribution

A Poissondistribution
plot.normal

Plotting a Probability Distribution
print.normal

Printing Probability Distributions
probabilitydensity

The Probability Density at a Value for a Continuous Distribution
precision

The Precision of a Distribution
mtdistribution

A Multivariate t-Distribution
posteriornormal2

Compute a Posterior Distribution for Parameters of Two Normal Distributions
betadistribution

A Beta Distribution
anovatable

Computes ANOVA table given data and design
contrast

Computing the distribution of a Contrast
betabinomial

Create an Object Representing a Beta-Binomial Distribution
expgamma

Create an ExpGamma distribution
conditional

The Conditional Distribution
cdf

Compute Cumulative Distribution Function
difference

Create Object Representing Difference Between Two Distributions
credibilityinterval

Compute Credibility Interval for a Univariate Distribution
designTwoGroups

Create a Design Matrix for Two Groups of Observations
expectation

Compute Expectation
compose

Building a new probability distribution from an old.
fdistribution

Create an F distribution
binomialdistribution

Create an Object Representing a Binomial Distribution
binomialbeta

Create an Object Representing a bivariate Binomial Beta Distribution
designManyGroups

Create a Design Matrix for Several Groups of Normal Observations
discretedistribution

Create Object Representing a Discrete Distribution
designBalanced

Create a Design Matrix for a Balanced Design
designFactorial

Create a Design Matrix for a Factorial Design