Research about chained functions

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SUMMARY

This discussion focuses on the analysis of chained functions representing two events, specifically examining the relationship between an imaginary function (f(1) = Prodrome of illness) and a real function (f(2) = illness activation). The conversation highlights the importance of Bayesian statistics for understanding the intersection of these functions and integrating conditional probability to predict real outcomes. Additionally, it draws parallels with physics, illustrating how imaginary and real components can interact, such as in the case of an ideal pendulum where potential energy is imaginary and kinetic energy is real.

PREREQUISITES
  • Understanding of Bayesian statistics
  • Familiarity with real and imaginary functions in mathematics
  • Basic knowledge of conditional probability
  • Concepts of energy in physics, particularly potential and kinetic energy
NEXT STEPS
  • Study Bayesian statistics in a clinical context
  • Explore the mathematical definitions of real and imaginary functions
  • Research conditional probability and its applications in predictive modeling
  • Examine examples of energy trade-offs in physics, particularly in oscillatory systems
USEFUL FOR

Researchers, statisticians, mathematicians, and anyone interested in the intersection of probability theory and real-world event prediction.

badr
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TL;DR
Imaginary and real analysis in combination with conditional probability applied to them.
I am looking for some academical concept to work on 3 parts :

1) Real and imaginary analysis of two functions describing 2 events

2) If the first event's function is imaginary and the second is real , how can we analyse the intersection that show how the imaginary function turned out predicting a real event ( sencond function)

3) how to integrate conditional probability to predict the real outcome.

Hint :
f(1) = imaginary : Prodrome of illness
f(2) = real : illness activated or activation phase
 
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I am not sure that you are using the words real, imaginary, analysis and function in the same way that mathematicians use them.

In particular what is the "function of an event", and what does it mean if it is "imagainary" as opposed to "real"?

Looking at your hint if you are interested in the relationship between the observation of prodromal symptoms in relation to any particular illness and the (diagnosis of the) onset of that illness then you will want to study Bayesian statistics: here is an introduction in a clinical context.
 
Not sure what you are asking for, but here is one idea that might work.
There are often trade-offs in physics where one component can be represented on the imaginary axis and the other can be represented on the real axis. Consider a simple ideal pendulum. Suppose the potential energy of the pendulum is imaginary and the kinetic energy is real. Since the total energy is constant, the two forms of energy are traded off in a way that allows the knowledge of its potential energy maximum to be used to predict its kinetic energy maximum at a later time. You can probably think of other examples.
 

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