[R-sig-Geo] Plotting probability exceedance

[r@i@1290 m@iii@g oii @im@com]

Hi Akos,
Thank you so much for this suggestion! Indeed, I have 25 data points in each column, and yes, the data are normally distributed. Using the pnorm function is actually quite useful, as well. To that end, could the values of exceedance probability from pnorm be somehow plotted against their associated precipitation thresholds on an xy plot, for example?
Another idea that came to mind is the use of Probability Density Functions, but can these really be used to graphically show exceedance probabilities?
Thanks, again!
-----Original Message-----
From: Bede-Fazekas Ákos <bfalevlist using gmail.com>
To: r-sig-geo using r-project.org
Sent: Wed, Feb 15, 2023 1:59 am
Subject: Re: [R-sig-Geo] Plotting probability exceedance

Hello,

You should know or make assumptions on the distribution of the 
precipitation. Let's say it is normally distributed (i.e. bell-shaped). 
Then you can calculate the probability of exceeding the quantile /q/ by
pnorm(q, mean, sd, lower.tail = FALSE).
If you have several spatial points and a lot of measurments (stored in 
columns of the sf/data.frame) for each of the points, then use
apply(X, MARGIN = 1, FUN = function(measurements) {return(pnorm(q, mean, 
sd, lower.tail = FALSE))})
and you can display the probabilities in a map.

HTH,
Ákos
__________
Ákos Bede-Fazekas
Centre for Ecological Research, Hungary

2023.02.15. 1:28 keltezéssel, rain1290--- via R-sig-Geo írta:
> Hi there,
> I have climate data pertaining to extreme precipitation, as well as carbon emissions associated with those precipitation values in a dataframe.
> The goal of my analysis would be to determine the probability of exceeding specific thresholds of precipitation extremes, as well as showing this graphically (I am imagining this by placing extreme precipitation on the the x-axis and exceedance probabilities on the y-axis).
> My question is if anyone has an idea how to approach this, or a good starting place? I have looked online, but there is nothing specific to really draw on.
> Thank you for your time, and I look forward to your response!
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