Questions tagged [relative-distribution]
Relative distribution methods, plots and decompositions, as discussed in Mark S. Handcock and Martina Morris: Relative Distribution Methods in the Social Sciences (Springer).
14
questions
2
votes
0answers
80 views
Estimation of Distributions with Fat Tails
I work on estimation of income distributions. When I have very high inequality situation I have these two options: Estimate a conventional distribution (e.g. generalize beta) where the parameters go ...
2
votes
3answers
2k views
Compare two distributions of large sizes and unequal variances where one distribution is heavily skewed
My data is from cells that are treated under two different conditions and then their response to the condition is measured by one output variable.
The cell populations in the two conditions are quite ...
4
votes
1answer
115 views
How to arrive at a specific formulation of the relative median deviation?
I am an economist currently working with this book: Frank Cowell - Measuring Inequality
On page 25 a formulation of the relative mean deviation is given as follows:
$$
M = 2 \left[ F\left(\bar{y}\...
1
vote
1answer
239 views
How to qualitatively describe distribution shapes
I have a distribution which looks a bit binomial, though with a cutoff, i.e.:
$P(x) = 0$ if $x \le 0$, rises to a bell-shaped peak at around $x=0.2%$, appears to tail off exponentially until an ...
14
votes
2answers
5k views
How can I group numerical data into naturally forming “brackets”? (e.g. income)
The following describes what I'm trying to accomplish, but it's possible an alternative problem statement can describe my goal:
I want to
divide the following numbers into groups where the ...
3
votes
2answers
281 views
Calculating Gini coefficient with unbound income brackets?
I need to compute the Gini coefficient on some population data arranged in income brackets: for example
$0->$1000 : 10000 people
$1000->$10000: 50000 people
...
6
votes
1answer
400 views
Are sample means for quantiles of sorted data unbiased estimators of the true means?
In studying income inequality, it is very common to look at sample means for deciles or quintiles of the sample, and to assume that the sample means are good estimators of the true means. In this ...
25
votes
6answers
8k views
What are good data visualization techniques to compare distributions?
I am writing my PhD thesis and I've realized that I rely excessively in box plots in order to compare distributions. Which other alternatives do you like for achieving this task?
I'd also like to ask ...
6
votes
1answer
3k views
Effective way to visualize net growth/profit/income?
A non-profit has donors with monthly commitments, which you can think of as subscriptions. What is the best way to show for each month new acquisitions, cancels, and net growth? The relationship is
<...
4
votes
1answer
2k views
Standardized mean decomposition (Oaxaca-Blinder decomposition)
How does standardized mean decomposition differ from the simpler dummy variable regression? How does the average in mean outcomes or interpretation of results attributable to a particular treatment or ...
3
votes
2answers
190 views
Is it possible to make quantitative comparisons using income inequality metrics?
I've calculated income inequality metrics (Gini/Hoover/Theil coefficients) for several populations. I know I can make claims like "this population has a higher Gini coefficient, so its distribution in ...
2
votes
1answer
122 views
Disagregating overall growth into contributing factors
I have a dataset with library document holdings per publicationyear, which I can query for the frequency of terms, subjects, etc. That allows me to construct times-series of the "popularity" of ...
6
votes
2answers
765 views
Measuring homogeneity across different spatial aggregations of data
I'm working with dataset of individual households that I aggregate into 'areas' using several different spatial configurations, from smaller to bigger.
These areas are then characterized by four ...
2
votes
4answers
538 views
Ranking distributional data by similarity
The question in short: What methods can be used to quantify distributional relationships between data when the distribution is unknown?
Now the longer story: I have a list of distributions and would ...
