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Sextus Empiricus
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Your image shows the sum of two functions which relates to a mixture distribution:

$$h(x) = a g(x) + (1-a) f(x)$$

(see also this discussion)

with

  • the continuous distribution:

$$g(x) = \begin{cases} \frac{1}{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

  • a triangular distribution:

$$f(x) = \begin{cases} 2 \frac{N-x}{(N-n)^2} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

You do not need to worry about the constant of integration since:

$$\begin{array}{rcl} \int_n^N h(x)dx &=& \int_n^N \underbrace{( a g(x) + (1-a) f(x))}_{=h(x)} dx \\ & = & \int_n^N a g(x) dx + \int_n^N (1-a) f(x) dx \\ & = & a \underbrace{\int_n^N g(x) dx}_{=1} + (1-a) \underbrace{\int_n^N f(x) dx}_{=1} \\ & = & a + (1-a) = 1 \end{array} $$


To get your figure you need to add 5/7 times the uniform (squarerectangular) distribution and 2/7 times the triangle distribution.

example

$$h(x) = \frac{5}{7} g(x) + \frac{2}{7} f(x) = \begin{cases} \frac{\frac{5}{7} + \frac{4}{7} \frac{N-x}{N-n} }{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

Your image shows the sum of two functions which relates to a mixture distribution:

$$h(x) = a g(x) + (1-a) f(x)$$

(see also this discussion)

with

  • the continuous distribution:

$$g(x) = \begin{cases} \frac{1}{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

  • a triangular distribution:

$$f(x) = \begin{cases} 2 \frac{N-x}{(N-n)^2} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

You do not need to worry about the constant of integration since:

$$\begin{array}{rcl} \int_n^N h(x)dx &=& \int_n^N \underbrace{( a g(x) + (1-a) f(x))}_{=h(x)} dx \\ & = & \int_n^N a g(x) dx + \int_n^N (1-a) f(x) dx \\ & = & a \underbrace{\int_n^N g(x) dx}_{=1} + (1-a) \underbrace{\int_n^N f(x) dx}_{=1} \\ & = & a + (1-a) = 1 \end{array} $$


To get your figure you need to add 5/7 times the uniform (square) distribution and 2/7 times the triangle distribution.

example

Your image shows the sum of two functions which relates to a mixture distribution:

$$h(x) = a g(x) + (1-a) f(x)$$

(see also this discussion)

with

  • the continuous distribution:

$$g(x) = \begin{cases} \frac{1}{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

  • a triangular distribution:

$$f(x) = \begin{cases} 2 \frac{N-x}{(N-n)^2} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

You do not need to worry about the constant of integration since:

$$\begin{array}{rcl} \int_n^N h(x)dx &=& \int_n^N \underbrace{( a g(x) + (1-a) f(x))}_{=h(x)} dx \\ & = & \int_n^N a g(x) dx + \int_n^N (1-a) f(x) dx \\ & = & a \underbrace{\int_n^N g(x) dx}_{=1} + (1-a) \underbrace{\int_n^N f(x) dx}_{=1} \\ & = & a + (1-a) = 1 \end{array} $$


To get your figure you need to add 5/7 times the uniform (rectangular) distribution and 2/7 times the triangle distribution.

example

$$h(x) = \frac{5}{7} g(x) + \frac{2}{7} f(x) = \begin{cases} \frac{\frac{5}{7} + \frac{4}{7} \frac{N-x}{N-n} }{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

Source Link
Sextus Empiricus
  • 86.4k
  • 6
  • 115
  • 301

Your image shows the sum of two functions which relates to a mixture distribution:

$$h(x) = a g(x) + (1-a) f(x)$$

(see also this discussion)

with

  • the continuous distribution:

$$g(x) = \begin{cases} \frac{1}{N-n} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

  • a triangular distribution:

$$f(x) = \begin{cases} 2 \frac{N-x}{(N-n)^2} & \quad \text{ for $ n \leq x\leq$ N } \\ 0 & \quad \text{otherwise}\end{cases}$$

You do not need to worry about the constant of integration since:

$$\begin{array}{rcl} \int_n^N h(x)dx &=& \int_n^N \underbrace{( a g(x) + (1-a) f(x))}_{=h(x)} dx \\ & = & \int_n^N a g(x) dx + \int_n^N (1-a) f(x) dx \\ & = & a \underbrace{\int_n^N g(x) dx}_{=1} + (1-a) \underbrace{\int_n^N f(x) dx}_{=1} \\ & = & a + (1-a) = 1 \end{array} $$


To get your figure you need to add 5/7 times the uniform (square) distribution and 2/7 times the triangle distribution.

example