newpainters

<p>The original painters data contain the subjective assessment, 
     on a 0 to 20 integer scale, of 54 classical painters. The
     newpainters data discretizes the subjective assessment by
     quartiles with thresholds 25%, 50%, 75%. The painters were 
     assessed on four characteristics: composition, drawing, 
     colour and expression.  The data is due to the Eighteenth century 
     art critic, de Piles.</p>

datasets

A framework that brings together an abundance of common
statistical models found across packages into a unified interface, and
provides a common architecture for estimation and interpretation, as well
as bridging functions to absorb increasingly more models into the
package. Zelig allows each individual package, for each
statistical model, to be accessed by a common uniformly structured call and
set of arguments. Moreover, Zelig automates all the surrounding building
blocks of a statistical work-flow--procedures and algorithms that may be
essential to one user's application but which the original package
developer did not use in their own research and might not themselves
support. These include bootstrapping, jackknifing, and re-weighting of data.
In particular, Zelig automatically generates predicted and simulated
quantities of interest (such as relative risk ratios, average treatment
effects, first differences and predicted and expected values) to interpret
and visualize complex models.

James Honaker

Zelig

Everyone's Statistical Software

Christine Choirat

Christopher Gandrud

Kosuke Imai

Gary King

Olivia Lau

Robert Treacy

IQSS Harvard University

newpainters function

<p>A table containing 5 variables ("Composition", "Drawing", "Colour", 
"Expression", and "School") and 54 observations.</p>

Format

The Discretized Painter's Data of de Piles — newpainters

The Discretized Painter's Data of de Piles

newpainters: The Discretized Painter's Data of de Piles

Description

Usage

Arguments

Format

References