Oranges

The data arose from five orange trees grown in Riverside,
California, during 1969-1973. The response is the trunk circumference,
in millimeters, and the predictor variable is time, in days. The
predictor variable has an arbitrary origin and was taken on December
31, 1968.

datasets

Set of tools for the statistical analysis of data using: (1) normal linear models; (2) generalized linear models; (3) negative binomial regression models as alternative to the Poisson regression models under the presence of overdispersion; (4) beta-binomial and random-clumped binomial regression models as alternative to the binomial regression models under the presence of overdispersion; (5) Zero-inflated and zero-altered regression models to deal with zero-excess in count data; (6) generalized nonlinear models; (7) generalized estimating equations for cluster correlated data.

Luis Hernando Vanegas

glmtoolbox

Set of Tools to Data Analysis using Generalized Linear Models

Luz Marina Rondón

Gilberto A. Paula

Oranges function

A data frame with 35 rows and 3 variables:<dl>
 <dt>Trunk</dt>
<dd>a numeric vector indicating the trunk circumference, in millimeters.</dd> <dt>Days</dt>
<dd>a numeric vector indicating the time, in days, since December 31, 1968.</dd> <dt>Tree</dt>
<dd>a numeric vector with the identifier of each orange tree.</dd>
</dl>

Format

Oranges — Oranges

A data frame with 35 rows and 3 variables:<dl>
 <dt>Trunk</dt>
<dd>a numeric vector indicating the trunk circumference, in millimeters.</dd>

 <dt>Days</dt>
<dd>a numeric vector indicating the time, in days, since December 31, 1968.</dd>

 <dt>Tree</dt>
<dd>a numeric vector with the identifier of each orange tree.</dd>


</dl>

Oranges: Oranges

Description

Usage

Arguments

Format

References

Examples