Losses come from a mixture of an exponential distribution with mean 100 with probability pand an exponential distribution with mean 10,000 with probability 1- p.Losses of 100 and 2000 are observed.Determine the likelihood function of p.0.01pe' (1– p)e0«(1– p)e 02-20-0.2(A)pe10010,00010010,000-20 (1– p)e 02ре (1- рје 00110,000(B)ре10010010,000pe, (1- p)e 0.01)20 (1– p)e02(C)рере10010,00010010,000Pel100(1– p)e-001(1– p)e-02-20(D)ре10,00010010,000e-0.2+100 10,000ee0.01-20(E)р.+100 10,000

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Answered: Losses come from a mixture of an…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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17 Four-week summer rainfall totals, in inches, in a section of the Midwestern United States have approximately a gamma distribution with a = 1.2 and = 3. (a) Find the mean, in inches, and variance of the four-week rainfall totals. E(X) = in V(X) = (b) What is the probability that the four-week rainfall total exceeds 6 inches? (Round your answer to four decimal places.)
Please give full explanation. Thank you.
4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob>ChiSq 0.0013* 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?
Standard Ultimate Survival Model says that the force of mortality equals Ho = A+ Bc" with A = 0.00022, B = 2.7 × 10-6, c = 1.124 %3D Let the annual interest rate be į = 0.05. %3D For a life (aged 17), the present value of a benefit of $1 payable immediately on death is a random variable, Z. Find P[Z > 0.3]
Consider an electronic component with a lifetime denoted by a random variable T which is modelled by an exponential distribution with a parameter of average lifetime B = 5. Part A: Exponential Distribution Write the probability that a component is still working after 5 years, as an expression: P(T > 5) = | dt Use t for T e() for exponential function ()! for factorial ( )*( ) for exponents • Help entering equations Part B: Probability Write the probability that a component is still working after 5 years, numerically: P(T > 5) = • Help entering equations Part C: Binomial Distribution Let X be the random variable representing the number of components that are still working after 5 years. Write the binomial distribution for at least 3 components that are still working, as an expression: P(X 2 3) = Use p for parameter p x for the value of the random variable X e() for exponential function C(n,x) for combination of "x out of n" (O! for factorial (O*) for exponents • Help entering equations…
4. When the Titanic sank in 1912, there were over 1,300 passengers aboard. A random sample of 50 passengers that were aboard is taken. The amount they paid for the voyage and whether or not they survived is recorded. A model is fit to predict the probability they survived when the ship sank is obtained. Survived Logistic Fit of Survived By Fare 1.00 0.75 0.50- 0.25- 50 4 Parameter Estimates 100 Term Intercept -1.404254 0.4353289 Fare 0.01246686 0.0097945 For log odds of Yes/No Fare Estimate Std Error ChiSquare 10.41 1.62 150 200 Prob> ChiSq 0.0013 0.2031 No Yes a) Suppose someone paid a fare of 25 pounds. Predict the probability they survived. b) How much would someone pay to have at least a 65% chance of survival?
I need help with this question, A and C are wrong and I don't know D
2 The operator of a pumping station has observed that demand for water during early afternoon hours has an approximately exponential distribution with mean 100 cfs (cubic feet per second). (a) Find the probability that the demand will exceed 250 cfs during the early afternoon on a randomly selected day. (Round your answer to four decimal places.) (b) What water-pumping capacity, in cubic feet per second, should the station maintain during early afternoons so that the probability that demand will exceed capacity on a randomly selected day is only 0.02? (Round your answer to two decimal places.) cfs
One tree in the study had a weight that exceeded its expected weight (according to the best fit curve) by more than that of any other tree. By how many tons did the trees actual weight exceed the expected weight for its height?
A technician suspect that the number of computer errors recorded per day in the LAN follows a Poisson distribution with a mean of 2 errors per day. Record of the number of errors per day for the past 260 days are shown in table below. Number of Number of Pr(X = x) E (0; – e;) Errors per days ei day 77 1 90 2 55 3 30 4 or more a. Test the hypothesis that the number of computer errors per day has the Poisson distribution with mean 2 at the 5% significance level. b. Find an approximate value of the p – value for the test statistics in (a). 8
Losses come from a mixture of an exponential distribution with mean 100 with probability p and an exponential distribution with mean 10,000 with probability 1– p. Losses of 100 and 2000 are observed. Determine the likelihood function of p. -0.01 pe (1– p)e“ pe 20 (1– p)e0² -0.2 (A) 100 10,000 100 10,000 pe (1– p)e“ -0.01 (B) pe (1– p)e02' 100 10,000 100 10,000 pe, (1- p)e0. 20 (1– p)eº -0.01 pe 100 -0.2 (C) pe 10,000 100 10,000 pe, (1- p)e 00i -0.01 (D) -20 ре (1– p)e02 100 10,000 100 10,000 e 0.01 +(1– p) e -20 (E) р. 100 10,000 100 10,000
The probability mass function of a discrete random variable Y is given by k y = 2, 3,4, 5 p(y) = { 6- y 0, PV) : elsewhere

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