How Do You Calculate the PDF for Mixed Weather-Dependent Demand Distributions?

In summary, the demand for raincoats has a uniform distribution between 0 and a on a sunny day, and between 0 and b on a rainy day. The overall demand PDF takes into account both scenarios, and is a combination of the PDF for a sunny day and the PDF for a rainy day, weighted by their respective probabilities.
  • #1
singhr
1
0

Homework Statement


demand for raincoats
demand X is uniform [0,a) on a sunny day and ~U[0,b) on a rainy day. its is stated that b>a. the probability it is a sunny day is 'p' and that it is a rainy day is '1-p' (p and 1-p are constants)
compute the pdf?

Homework Equations


f(x) = f(x/B)h(B)+f(x/G)h(G)


The Attempt at a Solution




so i get a overall demand pdf f(x) = (p/a)+((1-p)/b) 0<x<a

((1-p)/b) a<x<b

Is this correct? does the demand distribution on a rainy day change when we restrict it between 0 to a
 
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  • #2
as well?

Your attempt at a solution is on the right track, but there are a few things that need to be corrected.

Firstly, the demand for raincoats can only be between 0 and a on a sunny day, and between 0 and b on a rainy day. This means that the PDF should be 0 for any values of x that fall outside of these ranges.

Secondly, the overall demand PDF should take into account both the sunny and rainy day scenarios. This means that the PDF should be a combination of the PDF for a sunny day and the PDF for a rainy day, weighted by their respective probabilities (p and 1-p).

So the correct PDF would be:

f(x) = (p/a) for 0<x<a
(1-p)/b for a<x<b
0 for all other values of x
 

What is a mixed distribution?

A mixed distribution is a probability distribution that combines two or more different distributions. It can be thought of as a mixture of different distributions, each with its own weight or proportion.

What are the types of mixed distributions?

The two main types of mixed distributions are the mixture distribution and the compound distribution. A mixture distribution is a combination of two or more different distributions, while a compound distribution is a combination of a distribution and a random variable.

What is the difference between a mixture distribution and a compound distribution?

The main difference between a mixture distribution and a compound distribution is that a mixture distribution combines two or more distributions, while a compound distribution combines a distribution with a random variable. In other words, a mixture distribution has multiple components, while a compound distribution has a single component and a random variable.

What are some examples of mixed distributions?

An example of a mixture distribution is the normal mixture model, which combines multiple normal distributions to model a dataset that may have multiple subpopulations. An example of a compound distribution is the Poisson compound distribution, which combines a Poisson distribution with a random variable to model count data with a varying rate.

How are mixed distributions used in scientific research?

Mixed distributions are commonly used in scientific research, particularly in fields such as statistics, economics, and biology. They are used to model complex data that may have multiple underlying distributions or to account for uncertain or random factors in a dataset. Mixed distributions can also be used for data clustering, classification, and prediction.

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