bermuda.grass

Yields of bermuda grass for a factorial design of nutrients
nitrogen,
phosphorus, and potassium.

datasets

A collection of functions helpful in learning the basic tenets of Bayesian statistical inference.  It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions.  It contains MCMC algorithms for summarizing posterior distributions defined by the user.  It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.

Jim Albert

LearnBayes

Functions for Learning Bayesian Inference

bermuda.grass function

A data frame with 64 observations on the following 4 variables.<dl class="dl-horizontal">
 <dt>y</dt><dd>yield of bermuda grass in tons per acre</dd>
 <dt>Nit</dt><dd>level of nitrogen</dd>
 <dt>Phos</dt><dd>level of phosphorus</dd>
 <dt>Pot</dt><dd>level of potassium</dd>
 </dl>

Format

Bermuda grass experiment data — bermuda.grass

A data frame with 64 observations on the following 4 variables.<dl class='dl-horizontal'>
 <dt>y</dt><dd>yield of bermuda grass in tons per acre</dd>
 <dt>Nit</dt><dd>level of nitrogen</dd>
 <dt>Phos</dt><dd>level of phosphorus</dd>
 <dt>Pot</dt><dd>level of potassium</dd>
 </dl>

bermuda.grass: Bermuda grass experiment data

Description

Usage

Arguments

Format