Let $X_1, X_2$ and $X_3$ be expontial random varibles with paramtre $\beta_1, \beta_2$ and $\beta_3$ respectivly.
The PDF and CDF of $X_i$ for $x\geq 0$ are $f_{X_i}(x)$ and $F_{X_i}(x)$ given by
\begin{align} f_{X_i}(x)&=b_ie^{-x \beta_i} \\ F_{X_i}(x)&=1-e^{-x \beta_i}. \end{align}
I would like to find the CDF of random varible $Z$ define by
$$Z=X_1+\max\{X2,X3\}$$ for difrent parametre.
What is the CDF if $\beta_i=\beta$ for all $i\in\{1,2,3\}$?.
Thanks.
This is the type of problem that is not well-suited to manual solution, and which can benefit considerably from the assistance of a computer algebra system.
If $X_1$, $X_2$ and $X_3$ are independent $\text{Exponential}(b_i)$ random variables, then the joint pdf $f(x_1,x_2,x_3)$ is:
We seek the cdf of $Z = X_1 + \max(X_2,X_3)$, namely $P(Z<z)$.
This can be obtained immediately as:
which returns the cdf as:
... where I have used the
Probfunction from the mathStatica add-on to Mathematica to help automate the calculation (and as disclosure, of which I am one of the authors).Identical parameters
In the case where the $b_i$ are identical, the set-up is identical: simply replace each $b_i$ with $b$, which yields a much more elegant solution for the cdf:
$$F(z) = 2 e^{-b z} (\sinh (b z)-b z) \quad \quad \text{ for } z > 0$$
Monte Carlo check
It is always a good idea to test symbolic work by alternative methods. Here is a quick comparison of the theoretical pdf (red dashed curve) with the empirical pdf (squiggly blue curve - generated by Monte Carlo) when $b_1 = 10$, $b_2 = 0.4$, and $b_3 = 7$:
All looks good.