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Plot and fit exponential decay probability of population

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I have a population
were each value is the time were the respective element of the population "dies" with "NaN" being elements, that never "die".
I am looking for a way to plot the propability that an element "dies" by the funtion of time converging to the relative amount ('NaN') of elements "surviving" as well as to fit this with a exponential decay curve (I know from e.g. histfit, that my data resembles this behaviour).
I already tried to use the hazard function or to plot 1-cdf.
Thanks for advance.

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Peter Mühlenbrock
Peter Mühlenbrock on 23 Mar 2020
I got so far to fit the data without taking the amount of "NaN" into account.
dataObjs = findobj(gcf,'-property','YData');
Up until now the survival function converges to 0. How can i make it converge to the amount of "NaN" in "y"?

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Accepted Answer

the cyclist
the cyclist on 23 Mar 2020
You are correct to use the ecdf function. I think the piece you are missing is the use of the 'censoring' input. Take a look at the example Empirical Hazard Function of Right-Censored Data


Peter Mühlenbrock
Peter Mühlenbrock on 23 Mar 2020
Perfect, this is working now, thanks. How can I now extract the datapoints for further fitting including the bounds as a weighting factor for the fit? The way I did it above is giving me the upper bounds as yData
the cyclist
the cyclist on 23 Mar 2020
I'm not sure I fully understand your question. May I suggest you accept this answer, and then post a new question with a bit more detail about what you mean? I'll keep a lookout for it.

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