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[REVIEW]: ungroup: An R package for efficient estimation of smooth distributions from coarsely binned data #937
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To fix this do the following two things:
For a list of things I can do to help you, just type:
Just a few minor revision comments:
@rlbarter Thanks for your comments. See below my response.
The last point I will address in the next comment.
Consider the following problem:
Based on the info above we can not calculate the average age unless we know the age of every student. However, we can approximate it by building a histogram with 2 bars (
Now, if we would be able somehow to build a histogram with more bars, say 6 bars (
For more real-world example and explanation of the method see this article: https://academic.oup.com/aje/article/182/2/138/94562
Regarding the two examples, the difference is seen in the estimated groups and estimated counts:
> # Example 1 ---------------------- > M1 <- pclm(x, y, nlast) > head(fitted(M1)) [0,1) [1,2) [2,3) [3,4) [4,5) [5,6) 292.254945 47.567040 12.031104 5.101512 3.653694 3.801854 > # Example 2 ---------------------- > # ungroup even in smaller intervals > M2 <- pclm(x, y, nlast, out.step = 0.5) > head(fitted(M2)) [0,0.5) [0.5,1) [1,1.5) [1.5,2) [2,2.5) [2.5,3) 211.751314 80.583505 32.679931 14.663353 7.463173 4.379769
Note, in example 1 we are estimating intervals of length 1. In example 2 we are estimating intervals of length 0.5 using the same aggregate data.
Visually the difference can be seen like this:
> plot(M1, type = "s") > plot(M2, type = "s")
@karthik The Zenodo doi is: 10.5281/zenodo.1421648
As discussed with @arfon in
@mpascariu As @arfon noted earlier, it is very challenging to typeset accurately when using markdown + pandoc. Given that you also have such a short paper the accurate placement you seek would be very challenging (without inserting a lot of empty space and page breaks). You might have to mess with figure sizes to make it fit the way you seek.
I'll let @arfon weigh in but I think the paper looks fine the way it is.
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