horse: Horse-colic data

In GSE: Robust Estimation in the Presence of Cellwise and Casewise Contamination and Missing Data

Horse-colic data

Description

This is a modified version of the original data set (taken from UCI repository, see reference), where only quantitative variables are considered. This data set is about horse diseases where the task is to determine if the lesion of the horse was surgical or not. It contains rows with completely missing values except for ID and must be removed by the users. They are kept mainly for pedagogical purposes.

Usage

data(horse)

Format

A data frame with 368 observations on the following 7 variables are quantitative and 1 categorical. The first variable is a numeric id.

Hospital_Number	numeric id, i.e. the case number assigned to the horse (may not be unique if the horse is treated > 1 time)
Rectal_temperature	rectal temperature in degree celcius
Pulse	the heart rate in beats per minute; normal rate is 30-40 for adults
Respiratory_rate	respiratory rate; normal rate is 8 to 10
Nasogastric_reflux_PH	scale is from 0 to 14 with 7 being neutral; normal values are in the 3 to 4 range
Packed_cell_volume	the number of red cells by volume in the blood; normal range is 30 to 50
Total_protein	normal values lie in the 6-7.5 (gms/dL) range
Abdomcentesis_total_protein	Values are in gms/dL
surgical_leison	was the problem (lesion) surgical?; 1 = yes, 2 = no

Source

The original data have been taken from the Journal of Statistics Education Databases at

• http://archive.ics.uci.edu/ml/datasets/Horse+Colic,

References

Frank, A. & Asuncion, A. (2010). UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science.

Examples

## Not run: 
data(horse)
horse.cts <- horse[,-c(1,9)] ## remove the id and categorical variable
res <- GSE(horse.cts)
plot(res, which="dd", xlog10=TRUE, ylog10=TRUE)
getOutliers(res)

## End(Not run)

GSE documentation built on Dec. 28, 2022, 1:31 a.m.