R Dataset / Package texmex / portpirie
On this Quadstat.net statistics page, you will find information about the portpirie data set which pertains to Rain, wavesurge, portpirie and nidd datasets.. The portpirie data set is found in the texmex R package. You can load the portpirie data set in R by issuing the following command at the console data("portpirie"). This will load the data into a variable called portpirie. If R says the portpirie 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 portpirie R data set. The size of this file is about 662 bytes. You can share this page with this URL: http://tinyurl.com/rq694xm.
Feel free to try out any of the free statistical operations found on this page. They are broken up into instructional and analysis applications. Two neat features include PDF export and auto-generation of an R command file which you can copy and paste into R or R Studio. You can try as many operations as you like. Quadstat is great for elementary statistics classes. If you are an instructor, feel free create a data set for your students.
Rain, wavesurge, portpirie and nidd datasets.
Rainfall, wave-surge, Port Pirie and River Nidd data sets.
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
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.
The rain, wave-surge and Port Pirie datasets are used by Coles and appear in
ismev package. The River Nidd data appear in the
Copied from the
ismev package and the
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
Dataset imported from https://www.r-project.org.
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