Continuation of the previous exercise I sent a picture about. Suppose now that n = 4 and it is observed y = (y1, y2, y3, y4) = (5, 6, 2, 5). Calculate the value of the function > ⇒ f (y; λ) at a few points between [0, 7] (even at all integer points) and draw its graph (of course you can also draw the graph with e.g. R). Note: You can multiply the values of the function by e.g. 10000 to get to a more comfortable order of magnitude. With the help of the picture you have drawn, estimate which value of the parameter à has the highest probability of observations? Note: The function λ ⇒ f (y; λ) is often denoted L(^; y) and is called the credibility function of the model. In the second week, the concept of credibility will be explored in more detail.

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Hi, please help solve this. I wrote it in another platform as this does not have all marks I would need. Its sort of a follow up on the other question I asked. 

Continuation of the previous exercise I sent a picture about.
Suppose now that n = 4 and it is observed y = (y1, y2, y3, y4) = (5, 6, 2, 5). Calculate the value
of the function > ⇒ f (y; λ) at a few points between [0, 7] (even at all integer points) and draw
its graph (of course you can also draw the graph with e.g. R). Note: You can multiply the
values of the function by e.g. 10000 to get to a more comfortable order of magnitude. With the
help of the picture you have drawn, estimate which value of the parameter λ has the highest
probability of observations? Note: The function λ ⇒ f (y; λ) is often denoted L(λ; y) and is
called the credibility function of the model. In the second week, the concept of credibility will
be explored in more detail.
Transcribed Image Text:Continuation of the previous exercise I sent a picture about. Suppose now that n = 4 and it is observed y = (y1, y2, y3, y4) = (5, 6, 2, 5). Calculate the value of the function > ⇒ f (y; λ) at a few points between [0, 7] (even at all integer points) and draw its graph (of course you can also draw the graph with e.g. R). Note: You can multiply the values of the function by e.g. 10000 to get to a more comfortable order of magnitude. With the help of the picture you have drawn, estimate which value of the parameter λ has the highest probability of observations? Note: The function λ ⇒ f (y; λ) is often denoted L(λ; y) and is called the credibility function of the model. In the second week, the concept of credibility will be explored in more detail.
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