Question

A random variable Y follows Gumbel distribution, the CDF of which is: ?(? ≤ ?) =...

A random variable Y follows Gumbel distribution, the CDF of which is: ?(? ≤ ?) = ?^−?^−?. Simulate 10 random numbers from this distribution using the LCG: Xi = (171*X0 + 24316) mod 30269 where the seed value (X0) is 1914. Show necessary calculations

Homework Answers

Answer #1

Using the seed, we compute the following random numbers and the uniform random numbers (in (0,1)) using the relation that

uniform random number(u)=random number/30269.

Now equating Gumbel CDF with u, we get the sample y from Gumbel distribution as y=-log(-log(u)).

All these are computed in the following table:

For query in above, comment.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
A random variable Y follows a continuous uniform distribution from 0 to 4.   Express each question...
A random variable Y follows a continuous uniform distribution from 0 to 4.   Express each question using proper probability notation. Find probability by applying the area law i.e. draw the distribution, mark the event, shade the area, find the amount of shaded area. What is the probability random variable Y takes a value less than 3.2? P[Y < 3.2] =   What is the probability random variable Y falls below 1.2? P[Y < 1.2] =   What is the probability random variable...
Suppose a random variable X has cumulative distribution function (cdf) F and probability density function (pdf)...
Suppose a random variable X has cumulative distribution function (cdf) F and probability density function (pdf) f. Consider the random variable Y = X?b a for a > 0 and real b. (a) Let G(x) = P(Y x) denote the cdf of Y . What is the relationship between the functions G and F? Explain your answer clearly. (b) Let g(x) denote the pdf of Y . How are the two functions f and g related? Note: Here, Y is...
Suppose Y is a random variable that follows a binomial distribution with n = 25 and...
Suppose Y is a random variable that follows a binomial distribution with n = 25 and π = 0.4. (a) Compute the exact binomial probability P(8 < Y < 14) and the normal approximation to this probability without using a continuity correction. Comment on the accuracy of this approximation. (b) Apply a continuity correction to the approximation in part (a). Comment on whether this seemed to improve the approximation.
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and...
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and Y denote a random variable that has a Poisson distribution with parameter λ = 6. Additionally, assume that X and Y are independent random variables. Using the joint pdf function of X and Y, set up the summation /integration (whichever is relevant) that gives the expected value for X, and COMPUTE its value.
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and...
Let X denote a random variable that follows a binomial distribution with parameters n=5, p=0.3, and Y denote a random variable that has a Poisson distribution with parameter λ = 6. Additionally, assume that X and Y are independent random variables. Using the joint pdf function of X and Y, set up the summation /integration (whichever is relevant) that gives the expected value for X, and COMPUTE its value.
Suppose that X is continuous random variable with PDF f(x) and CDF F(x). (a) Prove that...
Suppose that X is continuous random variable with PDF f(x) and CDF F(x). (a) Prove that if f(x) > 0 only on a single (possibly infinite) interval of the real numbers then F(x) is a strictly increasing function of x over that interval. [Hint: Try proof by contradiction]. (b) Under the conditions described in part (a), find and identify the distribution of Y = F(x).
using r coding Let Y be the random variable defined by: Y = 1 with probability...
using r coding Let Y be the random variable defined by: Y = 1 with probability 0.10, 5 with probability 0.20 ,10 with probability 0.40, 15 with probability 0.20, 19 with probability 0.10 ) Write an R program to simulate NOBS observations of the random variable Y. For NOBS=10000, find the sample mean and sample standard deviation. Write an R program to simulate NGAME games. Using the sample results for a simulation with NGAME = 40000
A random variable X has the cumulative distribution function (cdf) given by F(x) = (1 +...
A random variable X has the cumulative distribution function (cdf) given by F(x) = (1 + e−x ) −1 , −∞ < x < ∞. (i) Find the probability density function (pdf) of X. (ii) Roughly, take 10 points in the range of x (5 points below 0 and 5 points more than 0) and plot the pdf on these 10 points. Does it look like the pdf is symmetric around 0? (iii) Also, find the expected value of X.
A random variable follows a binomial distribution with a probability of success equal to 0.69 For...
A random variable follows a binomial distribution with a probability of success equal to 0.69 For a sample size of N=11​, find the values below. a. the probability of exactly 3 successes b. the probability of 7 or more successes c. the probability of exactly 10 successes d. the expected value of the random variable
A Uniform[0, 10] is a continuous random variable Y which assumes any value between [0, 10]...
A Uniform[0, 10] is a continuous random variable Y which assumes any value between [0, 10] with equal chance, with density f(y) = 1/10 for all y ∈ [0, 10] and zero everywhere else. Check that it satisfies the properties that a density function should have. Find its distribution function F(y) for all y ∈ (−∞,∞) and show that it satisfies the properties that a distribution function should have.
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT