# R Dataset / Package DAAG / dengue

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## Visual Summaries

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<iframe src="https://embed.picostat.com/r-dataset-package-daag-dengue.html" frameBorder="0" width="100%" height="307px" />
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Documentation

On this Picostat.com statistics page, you will find information about the dengue data set which pertains to Dengue prevalence, by administrative region. The dengue data set is found in the DAAG R package. You can load the dengue data set in R by issuing the following command at the console data("dengue"). This will load the data into a variable called dengue. If R says the dengue data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the dengue R data set. The size of this file is about 250,766 bytes.

## Dengue prevalence, by administrative region

### Description

Data record, for each of 2000 administrative regions, whether or not dengue was recorded at any time between 1961 and 1990.

### Usage

data(dengue)

### Format

A data frame with 2000 observations on the following 13 variables.

humid

Average vapour density: 1961-1990

humid90

90th percentile of humid

temp

Average temperature: 1961-1990

temp90

90th percentile of temp

h10pix

maximum of humid, within a 10 pixel radius

h10pix90

maximum of humid90, within a 10 pixel radius

trees

Percent tree cover, from satellite data

trees90

90th percentile of trees

NoYes

Was dengue observed? (1=yes)

Xmin

minimum longitude

Xmax

maximum longitude

Ymin

minimum latitude

Ymax

maximum latitude

### Details

This is derived from a data set in which the climate and tree cover information were given for each half degree of latitude by half degreee of longitude pixel. The variable NoYes was given by administrative region. The climate data and tree cover data given here are 50th or 90th percentiles, where percetiles were calculates across pixels for an administrative region.

### Source

Simon Hales, Environmental Research New Zealand Ltd.

### References

Hales, S., de Wet, N., Maindonald, J. and Woodward, A. 2002. Potential effect of population and climate change global distribution of dengue fever: an empirical model. The Lancet 2002; 360: 830-34.

### Examples

str(dengue)
glm(NoYes ~ humid, data=dengue, family=binomial)
glm(NoYes ~ humid90, data=dengue, family=binomial)

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Dataset imported from https://www.r-project.org.

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