Finding a combination discrete and continuous cdf to make a new cdf

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SUMMARY

The discussion focuses on constructing a cumulative distribution function (CDF) F(x) that combines both discrete and continuous components. The CDF is defined as F(x)=0.25e^x for -∞ PREREQUISITES

  • Understanding of cumulative distribution functions (CDFs)
  • Knowledge of discrete and continuous probability distributions
  • Familiarity with exponential functions and their properties
  • Basic concepts of probability theory and integration
NEXT STEPS
  • Study the properties of discrete and continuous probability distributions
  • Learn about constructing piecewise functions in probability theory
  • Explore the concept of weighted averages in probability distributions
  • Review examples of combining discrete and continuous distributions in statistics
USEFUL FOR

Students in statistics, mathematicians working with probability theory, and anyone interested in understanding the combination of discrete and continuous distributions in CDFs.

bennyska
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Homework Statement


Let F(x)[itex]=\begin{cases}<br /> .25e^{x} & -\infty<x<0\\<br /> .5 & 0\leq x\leq1\\<br /> 1-e^{-x} & 1<x<\infty\end{cases}$. Find a CDF of discrete type, <i>F_d(x)</i> and of continuous type, <i>F_c(x)</i> and a number 0<a<1 such that <i>F(x)</i>=aF_d(x)+(1-a)F_c(x)[/itex]

Homework Equations





The Attempt at a Solution


don't really have any idea of where to begin. i have the answers in the book. any hint would be greatly appreciated.
 
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fc will be continuous, but still will need to be defined explicitly for each interval

use the discrete probabilities to account for the discontinuities in the current function at x=0,1
 

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