![Suppose that we observe the continuous random variable X - (X1,... ,Xn) with state space S, whose distribution we do not know but we are assuming that its p.d.f. belongs to a known family of distributions {fo: θ Ε Θ. We construct an estimator for the unknown parameter θ(X) (a) Explain why it is wrong to write (oox) and correct it. [2 marks]](http://img.homeworklib.com/questions/49ce1b90-62ba-11ea-9726-4741282e90c3.png?x-oss-process=image/resize,w_560)
I'm not sure if there any differences in writing E(^θ(X)) and E(^θ)......If not, why is the above format wrong?
I'm confused what the question is asking.....I have no idea what kind of parameters the cost function depends on.....Also, refer to the exact optimisation problem, is it saying the situation is unbiased? But then, what is the range of these parameters?
A lot of thanks if you could answer my questions!
Homework Answers
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I'm not sure if there any differences in writing E(^θ(X)) and
E(^θ)......If not, why is the...
2 Suppose that we observe the continuous random variable X (X1,.., Xn) with state space S,...
2 Suppose that we observe the continuous random variable X (X1,.., Xn) with state space S, whose distribution we do not know but we are assuming that its p.d.f. belongs to a known family of distributions {fe;Be Θ). We construct an estimator for the unknown parameter θ(X) (a) Explain why it is wrong to write E(ex) and correct it. 12 marks (b) Explain the difference between pdf and likelihood function. [1 mark] (c) Explain the different between estimate and estimator....
Assume that we have three independent observations: where Xi ~ Binomial(n 7,p) for i E { 1.2.3). The value of p E (0, 1) is not known. When we have observations like this from different, independent...
Assume that we have three independent observations: where Xi ~ Binomial(n 7,p) for i E { 1.2.3). The value of p E (0, 1) is not known. When we have observations like this from different, independent ran- dom variables, we can find joint probabilities by multiplying together th ndividual probabilities. For example This should remind you the discussion on statistical independence of random variables that can be found in the course book (see page 22) Answer the following questions a...
wthout insunnce coverage? The text ook aplans inutvely why te risk-areธe consumer brys nsurance; tis homework...
wthout insunnce coverage? The text ook aplans inutvely why te risk-areธe consumer brys nsurance; tis homework assgment uses a simple numerical exampia.) If losses are uitrmy dstrbutad frm 0 to average loss, as we wored out oarier? The actuarial pure prem um is 1% of the awengo loss. This should bo haf the pure premium of the sconato whon al losses are total bsas) Microoconomics, Module 24, Risk and Uncortainty (Chapter 18) Hamowark The atadhed PDFfie has better formating-) Rek...
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Risk management in Information Security today Everyday information security professionals are bombarded with marketing messages around risk and threat management, fostering an environment in which objectives seem clear: manage risk, manage threat, stop attacks, identify attackers. These objectives aren't wrong, but they are fundamentally misleading.In this session we'll examine the state of the information security industry in order to understand how the current climate fails to address the true needs of the business. We'll use those lessons as a foundation...
2 Suppose that we observe the continuous random variable X (X1,.., Xn) with state space S, whose distribution we do not know but we are assuming that its p.d.f. belongs to a known family of distributions {fe;Be Θ). We construct an estimator for the unknown parameter θ(X) (a) Explain why it is wrong to write E(ex) and correct it. 12 marks (b) Explain the difference between pdf and likelihood function. [1 mark] (c) Explain the different between estimate and estimator....
Assume that we have three independent observations: where Xi ~ Binomial(n 7,p) for i E { 1.2.3). The value of p E (0, 1) is not known. When we have observations like this from different, independent ran- dom variables, we can find joint probabilities by multiplying together th ndividual probabilities. For example This should remind you the discussion on statistical independence of random variables that can be found in the course book (see page 22) Answer the following questions a...
wthout insunnce coverage? The text ook aplans inutvely why te risk-areธe consumer brys nsurance; tis homework assgment uses a simple numerical exampia.) If losses are uitrmy dstrbutad frm 0 to average loss, as we wored out oarier? The actuarial pure prem um is 1% of the awengo loss. This should bo haf the pure premium of the sconato whon al losses are total bsas) Microoconomics, Module 24, Risk and Uncortainty (Chapter 18) Hamowark The atadhed PDFfie has better formating-) Rek...
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