A new optimization parameter in a statistical sample !

A new optimization parameter in a statistical sample !

I just thought up a new citation index parameter. Its very interesting check this out.

It reflects the quality scope of the citations. Its the total percentage of a citation that goes into defining a particular citation index. Let me call it q-index therefore (q for quality)

See this example.

My h-ind is 60. So total (minimum) citation it accounts for is 60*60 = 3600. My total citation is 12215. So my q-ind is 3600/12215 = 29.47% Or 29.47% of my total citation were important for this parameter. Hence my q-index is 29.47. In this way if someone has 5000 total citation with h-index 60, he has a much better q-index than mine, because more of his paper are highly cited. [his would be 72% vs mine 30%, we both have h-index 60 but his q-index is 72 and mine 30, considered for the same index-type; h.]

Now my i10-index is 174. It takes therefore 174*10 = 1740 out of 12215 citations. So quality is less. The q-index is now 1740/12215 = 14.24% or q-ind = 14.24.

See that my i10 index compared to my h-index is a low quality measure of my citations. While the number is bigger (174 > 60 ) the actual area of citation it covers is less.

Note that the q-index needs be corrected in the sense that the actual percentage will differ since some papers will have lets say 80 citations (in the h-index 60 list) and some will have 30 citation in the i10-ind list)

But for minimal considerations, h-ind 60 q-ind 29.47 says 30% at-least of total citations have been consequential. For i10 = 174 on the other hand only 14.24 % is consequential. When we have more info (which is available in determining h or i10) q-index tells us what percentage of citation indices are actually consequential.

One can then normalize different indices to a particular q-index value to say how to scale an index (h or i10 or g eg) to its q-index optimized value.

So if I scale the optimization of q to lets say 35% (because for different people/sample the q will differ, so I first scale everyone to a particular value) then I can compare the h-ind, i10 and g etc of different people or sample.

For person A h-ind is having a consequential quality of 30% and for person B its at 45% then they need to be re-normalized first? According to the q-index as a percentage of citations that have been counted. As simple as a b c ..

I am an experimental particle physicist, traveler, teacher, researcher, scientist and communicator of ideas. I am a quarkist and a bit quirky ! Hypothesis non fingo, eppur si muove, dubito cogito ergo sum are things that turn me on ! Researcher in experimental high energy physics (aka elementary particle physics; like “quarks, leptons & mesons and baryons”) … Teacher of Physics (and occasionally chemistry and maths) Blogger (check my website; mdashf.org) ! Love to read read and read but only stuff that interest me. Love to puff away my time in frivolities, just dreaming and may be thinking. Right now desperately trying to streamline myself.

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