2. Consider a random sample X1,..., Xn from a normal distribution with known mean 0 and unknown variance 0 = o? (a) Write the likelihood and log-likelihood function (b) Derive the maximum likelihood estimator for 0 (c) Show that the Fisher information matrix is I(0) = , (d) What is the variance of the maximum likelihood estimator for 0? Does it attain the Cramer-Rao lower bound?

2. Consider a random sample X1,..., Xn from a normal distribution with known mean 0 and unknown variance 0 = o? (a) Write the likelihood and log-likelihood function (b) Derive the maximum likelihood estimator for 0 (c) Show that the Fisher information matrix is I(0) = , (d) What is the variance of the maximum likelihood estimator for 0? Does it attain the Cramer-Rao lower bound?

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

REM (rapid eye movement) sleep is sleep during which most dreams occur. Each night a person has both REM and non-REM sleep. However, it is thought that children have more REM sleep than adultst. Assume that REM sleep time is normally distributed for both children and adults. A random sample of n, = 8 children (9 years old) showed that they had an average REM sleep time of x, = 2.9 hours per night. From previous studies, it is known that o, = 0.6 hour. Another random sample of n, = 8 adults showed that they had an average REM sleep time of x2 = 2.10 hours per night. Previous studies show that o, = 0.7 hour. Do these data indicate that, on average, children tend to have more REM sleep than adults? Use a 1% level of significance. (a) What is the level of significance? State the null and alternate hypotheses. O Ho: H1 = H2i HiitHy> H2 O Ho: H,
Suppose the variance of a regression model's stochastic error term is given by: Var(e;) = o = 2.5, i= 1,.,N %3D %3D ... Then: the observations of the stochastic error term are serially correlated. the observations of the stochastic error term are heteroskedastic. the OLS estimators of the model's parameters are definitely not BLUE. O the "proportionality factor" is V2.5. O None of the above are true statements.
Consider the following regression model: Yi = B1 + B2X2i + ß3X3i + ß4X4i + ui Using the model above show that the maximum likelihood estimator for the variance, var (ui||X2i, X3i, B4X4i), is biased (be sure to comment of the nature of the bias).
The average age at which adolescent girls reach their adult height is 16 years. Suppose you have a sample of 29 adolescent girls who are developmentally delayed, and who have an average age at which they reached their adult height of 17.8 years and a sample variance of 77.4 years. You want to test the hypothesis that adolescent girls who are developmentally delayed have a different age at which they reached their adult height than all adolescent girls. In order to calculate the t statistic, you first need to calculate the estimated standard error. The estimated standard error SM = (round to four decimals)
please send solution for part c and d
A snack food manufacturer estimates that the variance of the number of grams of carbohydrates in servings of its tortilla chips is 1.34. A dietician is asked to test this claim and finds that a random sample of 16 servings has a variance of 1.22. At α=0.05, is there enough evidence to reject the manufacturer's claim? Assume the population is normally distributed. Complete parts (a) through (e) below.
If the coefficient B₁ has a nonzero value, then it is helpful in predicting the value of the response variable. If B₁ = 0, it is not helpful in predicting the value of the response variable and can be eliminated from the regression equation. To test the claim that B₁ = 0 use the test statistic t = (b₁-0) /sp. Critical values or P-values can be found using the t distribution with n - (k+1) degrees of freedom, where k is the number of predictor (x) variables and n is the number of observations in the sample. The standard error sp, is often provided by software. For example, see the accompanying technology display, which shows that sp=0.076885101 (found in the column with the heading of "Std. Err." and the row corresponding to the first predictor variable of height). Use the technology display to test the claim that B₁ = 0. Also test the claim that B₂ = 0. What do the results imply about the regression equation? Click the icon to view the technology output. Test the claim that B₁ = 0. For…
Imagine a family member looks over your shoulder as you look at the variance equation Σki=1(xi − μ)2P(X = xi) and asks why the P(X = xi) term is there. What would you say?
The average age at which adolescent girls reach their adult height is 16 years. Suppose you have a sample of 29 adolescent girls who are developmentally delayed, and who have an average age at which they reached their adult height of 17.8 years and a sample variance of 77.4 years. You want to test the hypothesis that adolescent girls who are developmentally delayed have a different age at which they reached their adult height than all adolescent girls. In order to calculate the t statistic, you first need to calculate the estimated standard error. The estimated standard error SM= (round to four decimals)
4) In a univariate linear regression, explain intuitively, graphically and mathematically, how the variance of the estimated slope depends on a) the number of observations; b) the mean squared deviation of the independent variable; c) What else does it depend on? Can you explain how?
3
There are 3000 stocks in the long-short stock market, which will be traded for 250 days in the next year. Set X and Y to be the daily holding amount of each stock And the return of the next day, and X and Y are respectively sampled from the normal distribution of N (0.100000NO, 2E-2). Use enough data to estimate Calculate the R2 of X and Y linear regression to be 001. Assume that positions among stocks are not correlated, and returns between stocks are not correlated. Define a day’s PNL as the day’s receipt beneficial PNL= 3000∑xy Find the expectation of PN and the sharpe rate of PNL every day