R Dataset / Package texmex / rain

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

Stem and Leaf Plots

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Visual Summaries

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<iframe src="https://embed.picostat.com/r-dataset-package-texmex-rain.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-17814.csv 52.28 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the rain data set which pertains to Rain, wavesurge, portpirie and nidd datasets.. The rain data set is found in the texmex R package. You can load the rain data set in R by issuing the following command at the console data("rain"). This will load the data into a variable called rain. If R says the rain data set is not found, you can try installing the package by issuing this command install.packages("texmex") 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 rain R data set. The size of this file is about 53,535 bytes.

Documentation

Rain, wavesurge, portpirie and nidd datasets.

Description

Rainfall, wave-surge, Port Pirie and River Nidd data sets.

Format

The format of the rain data is: num [1:17531] 0 2.3 1.3 6.9 4.6 0 1 1.5 1.8 1.8 ...

The wave-surge data is bivariate and is used for testing functions in texmex.

The Port Pirie data has two columns: 'Year' and 'SeaLevel'.

The River Nidd data represents 154 measurements of the level of the River Nidd at Hunsingore Weir (Yorkshire, UK) between 1934 and 1969. Each measurement breaches the threshold of $65 m^3/2$. Various authors have analysed this dataset, as described by Papastathopoulos and Tawn~egp, there being some apparent difficulty in identifying a threshold above which GPD models are suitable.

Details

The rain, wave-surge and Port Pirie datasets are used by Coles and appear in the ismev package. The River Nidd data appear in the evir package.

Source

Copied from the ismev package and the evir package

References

S. Coles, An Introduction to Statistical Modeling of Extreme Values, Springer, 2001

I. Papastathopoulos and J. A. Tawn, Extended Generalised Pareto Models for Tail Estimation, Journal of Statistical Planning and Inference, 143, 134 – 143, 2011

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

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