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Let Yı, Y2, Ys, and Y4 be independent, identically distributed random variables from a mean u...
Let Yı, Y2, Ys, and Y4 be independent, identically distributed random variables from a mean u and a variance 02. Consider a different estimator of u: W=Y+Y2+2Y3+ Y 00 This is an example of a weighted average of the Y a) Show that W is a linear estimator. b) Is W an unbiased estimator of u? Show that it is - or it isn't (E(W) = Find the variance of W and compare it to the variance of the sample...
Suppose that X1, X2,.... Xn and Y1, Y2,.... Yn are independent random samples from populations with...
Suppose that X1, X2,.... Xn and Y1, Y2,.... Yn are independent random samples from populations with the same mean μ and variances σ., and σ2, respectively. That is, x, ~N(μ, σ ) y, ~ N(μ, σ ) 2X + 3Y Show that is a consistent estimator of μ.
3. You have two independent random samples: XiXX from a population with mean In and variance σ2 a...
3. You have two independent random samples: XiXX from a population with mean In and variance σ2 and Y, Y2, , , , , Y,n from a population with mean μ2 and variance σ2. Note that the two populations share a common variance. The two sample variances are Si for the first sample and Si for the second. We know that each of these is an unbiased estimator of the common population variance σ2, we also know that both of...
Question 6 Let X1, . . . , Xn denote a sequence of independent and identically...
Question 6 Let X1, . . . , Xn denote a sequence of independent and identically distributed i.id. N(14x, σ2) random variables, and let Yı, . . . , Yrn denote an independent sequence of iid. Nụy, σ2) ran- dom variables. il Λί and Y is an unbiased estimator of μ for any value of λ in the unit interval, i.e. 0 < λ < 1. 2. Verify that the variance of this estimator is minimised when and determine the...
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(...
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown. Let ρ-r/of and g m/n, and consider the problem of unbiased estimation of u
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown....
QUESTION 5 Suppose that Yı, Y2,.., Yn independent variables such that where β is an unknown...
QUESTION 5 Suppose that Yı, Y2,.., Yn independent variables such that where β is an unknown parameter, X1, x2-.., xn are known real numbers, and el,e2 independent random errors each with a normal distribution with mean 0 and variance ơ2 ,en are (a) Show that is an unbiased estimator of β. What is the variance of the estimator? (b) Given that the probability density function of Y is elsewhere, show that the maximum likelihood estimator of β is not the...
Suppose that Y1 , Y2 ,..., Yn denote a random sample of size n from a...
Suppose
that Y1 , Y2 ,..., Yn denote a random sample of size n from a
normal population with mean μ and variance 2 .
Problem # 2: Suppose that Y , Y,,...,Y, denote a random sample of size n from a normal population with mean u and variance o . Then it can be shown that (n-1)S2 p_has a chi-square distribution with (n-1) degrees of freedom. o2 a. Show that S2 is an unbiased estimator of o. b....
Can anyone explain blue writing? Thank you!! Let Yı and Y2 be independent, Normal random variables,...
Can anyone explain blue writing? Thank you!!
Let Yı and Y2 be independent, Normal random variables, each with mean μ and variance σ2 . Let a1 and a2 denote known constants. _Find the density function of the linear combination a1 Y1 + a2 γ2. Do we ALWAYS use momentume generating function? The mgfforaNormal distribution with parameters μ and σ is m(t) = 、 @t+σ2t2/2» ls this just a formula that l have to remember?? Ele(aYjke(ph)t] Ele a Y)Ele Y2)]I understood...
1. Let Yı,Y2,..., Yn denote a random sample from a population with mean E (-0,) and...
1. Let Yı,Y2,..., Yn denote a random sample from a population with mean E (-0,) and variance o2 € (0,0). Let Yn = n- Y. Recall that, by the law of large numbers, Yn is a consistent estimator of . (a) (10 points) Prove that Un="in is a consistent estimator of . (b) (5 points) Prove that Vn = Yn-n is not a consistent estimator of (c) (5 points) Suppose that, for each i, P(Y, - of ? Prove what...
6.81 Let Yı, Y. ..., Y, be independent, exponentially distributed random variables with mean B. a...
6.81 Let Yı, Y. ..., Y, be independent, exponentially distributed random variables with mean B. a Show that Y) = min(Y , Y2, ..., Y,) has an exponential distribution, with mean B/n. b If n = 5 and B = 2, find P(Ym <3.6).
Let Yı, Y2, Ys, and Y4 be independent, identically distributed random variables from a mean u and a variance 02. Consider a different estimator of u: W=Y+Y2+2Y3+ Y 00 This is an example of a weighted average of the Y a) Show that W is a linear estimator. b) Is W an unbiased estimator of u? Show that it is - or it isn't (E(W) = Find the variance of W and compare it to the variance of the sample...
Suppose that X1, X2,.... Xn and Y1, Y2,.... Yn are independent random samples from populations with the same mean μ and variances σ., and σ2, respectively. That is, x, ~N(μ, σ ) y, ~ N(μ, σ ) 2X + 3Y Show that is a consistent estimator of μ.
3. You have two independent random samples: XiXX from a population with mean In and variance σ2 and Y, Y2, , , , , Y,n from a population with mean μ2 and variance σ2. Note that the two populations share a common variance. The two sample variances are Si for the first sample and Si for the second. We know that each of these is an unbiased estimator of the common population variance σ2, we also know that both of...
Question 6 Let X1, . . . , Xn denote a sequence of independent and identically distributed i.id. N(14x, σ2) random variables, and let Yı, . . . , Yrn denote an independent sequence of iid. Nụy, σ2) ran- dom variables. il Λί and Y is an unbiased estimator of μ for any value of λ in the unit interval, i.e. 0 < λ < 1. 2. Verify that the variance of this estimator is minimised when and determine the...
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown. Let ρ-r/of and g m/n, and consider the problem of unbiased estimation of u
In 10. 11, Let X1, X2, . , Xn and Yi, Y2, . . . , Y,, be independent samples from N(μ, σ?) and N(μ, σ), respectively, where μ, σ. ơỈ are unknown....
QUESTION 5 Suppose that Yı, Y2,.., Yn independent variables such that where β is an unknown parameter, X1, x2-.., xn are known real numbers, and el,e2 independent random errors each with a normal distribution with mean 0 and variance ơ2 ,en are (a) Show that is an unbiased estimator of β. What is the variance of the estimator? (b) Given that the probability density function of Y is elsewhere, show that the maximum likelihood estimator of β is not the...
Suppose
that Y1 , Y2 ,..., Yn denote a random sample of size n from a
normal population with mean μ and variance 2 .
Problem # 2: Suppose that Y , Y,,...,Y, denote a random sample of size n from a normal population with mean u and variance o . Then it can be shown that (n-1)S2 p_has a chi-square distribution with (n-1) degrees of freedom. o2 a. Show that S2 is an unbiased estimator of o. b....
Can anyone explain blue writing? Thank you!!
Let Yı and Y2 be independent, Normal random variables, each with mean μ and variance σ2 . Let a1 and a2 denote known constants. _Find the density function of the linear combination a1 Y1 + a2 γ2. Do we ALWAYS use momentume generating function? The mgfforaNormal distribution with parameters μ and σ is m(t) = 、 @t+σ2t2/2» ls this just a formula that l have to remember?? Ele(aYjke(ph)t] Ele a Y)Ele Y2)]I understood...
1. Let Yı,Y2,..., Yn denote a random sample from a population with mean E (-0,) and variance o2 € (0,0). Let Yn = n- Y. Recall that, by the law of large numbers, Yn is a consistent estimator of . (a) (10 points) Prove that Un="in is a consistent estimator of . (b) (5 points) Prove that Vn = Yn-n is not a consistent estimator of (c) (5 points) Suppose that, for each i, P(Y, - of ? Prove what...
6.81 Let Yı, Y. ..., Y, be independent, exponentially distributed random variables with mean B. a Show that Y) = min(Y , Y2, ..., Y,) has an exponential distribution, with mean B/n. b If n = 5 and B = 2, find P(Ym <3.6).
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