On this Picostat.com statistics page, you will find information about the nidd data set which pertains to Rain, wavesurge, portpirie and nidd datasets.. The nidd data set is found in the texmex R package. Try to load the nidd data set in R by issuing the following command at the console data("nidd"). This may load the data into a variable called nidd. If R says the nidd 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 with library("texmex") followed by data("nidd"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing nidd at the command-line which should display the entire dataset.
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 nidd R data set. The size of this file is about 952 bytes.
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 –
Dataset imported from https://www.r-project.org.