Question

use R software Suppose that X1, …, Xn are a random sample from a lognormal distribution....

use R software

Suppose that X1, …, Xn are a random sample from a lognormal distribution. Construct a 95% confidence interval for the parameter μ. Use a Monte Carlo method to obtain an empirical estimate of the confidence level when data is generated from standard lognormal.

Homework Answers

Answer #1

Output:

2.5% 97.5%
0.9804272 1.0195226

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
Use R statistical software to answer the following: Let X1, ..., X6 be a random sample...
Use R statistical software to answer the following: Let X1, ..., X6 be a random sample of size n = 6 from the distribution with pdf f(x) = x / 8 , 0 < x < 4 and 0 otherwise. (a) Use Monte Carlo to calculate Var(Xbar), and knowing that Var(Xbar) = sigma^2 / n, what is the true value of Var(Xbar)? ## use runif() to generate samples
6. Let X1, X2, ..., Xn be a random sample of a random variable X from...
6. Let X1, X2, ..., Xn be a random sample of a random variable X from a distribution with density f (x)  ( 1)x 0 ≤ x ≤ 1 where θ > -1. Obtain, a) Method of Moments Estimator (MME) of parameter θ. b) Maximum Likelihood Estimator (MLE) of parameter θ. c) A random sample of size 5 yields data x1 = 0.92, x2 = 0.7, x3 = 0.65, x4 = 0.4 and x5 = 0.75. Compute ML Estimate...
Suppose that X1,..., Xn form a random sample from the uniform distribution on the interval [0,θ],...
Suppose that X1,..., Xn form a random sample from the uniform distribution on the interval [0,θ], where the value of the parameter θ is unknown (θ>0). (1)What is the maximum likelihood estimator of θ? (2)Is this estimator unbiased? (Indeed, show that it underestimates the parameter.)
Suppose X1 ...... Xn is a random sample from the uniform distribution on [a; b]. (a)...
Suppose X1 ...... Xn is a random sample from the uniform distribution on [a; b]. (a) Find the method of moments estimators of a and b. (b) Find the maximum likelihood estimators of a and b. please step by step
Use R. Generate a random sample with n=15 random observations from an exponential distribution with mean=1....
Use R. Generate a random sample with n=15 random observations from an exponential distribution with mean=1. Calculate the sample median, which is an estimator of the population median. Use bootstrap (nonparametric, with B=1000) methods to estimate the variance of the estimator for the population median. use the Monte Carlo method, e.g. generate 1000 samples of size 15 to estimate the true variance of the median estimator. Compare and comment on your results.
Suppose that (X1, · · · , Xn) is a random sample from uniform distribution U(0,...
Suppose that (X1, · · · , Xn) is a random sample from uniform distribution U(0, θ). (a) Prove that T(X1, · · · , Xn) = X(n) is minimal sufficient for θ. (X(n) is the largest order statistic, i.e., X(n) = max{X1, · · · , Xn}.) (b) In addition, we assume θ ≥ 1. Find a minimal sufficient statistic for θ and justify your answer.
use R software Let X be a non-negative random variable with μ = E[X] < ∞....
use R software Let X be a non-negative random variable with μ = E[X] < ∞. For a random sample x1, …, xn from the distribution of X, the Gini ratio is defined by G=12n2μn∑j=1n∑i=1|xi−xj|.G=12n2μ∑j=1n∑i=1n|xi−xj|. The Gini ratio is applied in economics to measure inequality in income distribution (see, e.g., [168]). Note that G can be written in terms of the order statistics x(i) as G=1n2μn∑i=1(2i−n−1)x(i).G=1n2μ∑i=1n(2i−n−1)x(i). If the mean is unknown, let ˆGG^ be the statistic G with μ replaced...
Suppose that we have a random sample X1, ** , Xn drawn from a distribution that...
Suppose that we have a random sample X1, ** , Xn drawn from a distribution that only takes positive values. Suppose that the sample size n is sufficiently large. Consider the new random variable ∏ n i=1 Xi . Derive the distribution of this new random variable and explain your reasoning mathematically
Suppose that we have a random sample X1, · · , Xn drawn from a distribution...
Suppose that we have a random sample X1, · · , Xn drawn from a distribution that only takes positive values. Suppose that the sample size n is sufficiently large. Consider the new random variable ∏ n i=1 Xi . Derive the distribution of this new random variable and explain your reasoning mathematically
Suppose that X1,...,Xn ∼ U(0,θ); that is, a sample of N observations from a random variable...
Suppose that X1,...,Xn ∼ U(0,θ); that is, a sample of N observations from a random variable with a uniform distribution where the lower bound is 0 and the upper bound θ is unknown. Find the maximum likelihood estimate of θ, also demonstrating this in R. Draw the pdf and the likelihood, and explain what they represent, in R.
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT