Get the latest business insights from Dun & Bradstreet. Theil Consulting GmbH of Hemmoor, Niedersachsen. Geom_abline(intercept = Sumq, slope = Sumq, color="red", size=1. Find company research, competitor information, contact details & financial data for Dr. # Quantile Regression Analysis of Deviance Table Model.null = rq(MinTemp ~ 1, data = Data, tau = 0.5) Model.q = rq(MinTemp ~ Year, data = Data, tau = 0.5) As a note, this problem does not occur with the quantile regression shown below with red line.ĭata are approximate. I don't know why this would be, but I also don't know how mblm calculates the intercept. There is an example in the command help and Code: ineqdeco decileincome fwpopulation, by (region) may be closer to what you want. The advice by helps: set 1950 as Year 0, and the results are much more reasonable. Compared to the Gini index, it has the advantage of being additive across different subgroups or regions in the country. It is a special case of the generalized entropy index. While the troops landed further north, the fleet, under the command of Admiral Lonq, tried to force an entrance to the harbour but his ships were repulsed. Theil Index, GE(1) The Theil index is part of a larger family of measures referred to as the General Entropy class. 2 The basic Theil index T T is the same as redundancy in information theory which is the maximum possible entropy of the data minus the observed entropy. 1 It has also been used to measure the lack of racial diversity.
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The intercept seems high, and while I know it is based on the median of pairs rather than the average, that trend line just does not sit right with me. Decomposition of drivers of world inequality across categories (Theil index). The Theil index is a statistic used to measure economic inequality. I used Tom's advice and got the following:
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Can someone help me understand this result and help me figure out how to plot the trend and observed data together? I don't understand why I am getting this result, not only from a plotting standpoint (as it would not line up with the data at all) but also given what I know about the median method used to calculate this intercept. I get statistically significant slopes of around 0.0148, but the intercept is always. When I use different packages in R (trend, mlblm, and this one: ) As you can see in the figure, I have a time series of averaged yearly minimum temperatures across over 30 stations over 50 years ranging between 5 and 10 degrees C:
So I am simply trying to plot observed data and the Theil-Sen trend estimate on one plot, but the estimates have been strange but consistent across methods/packages.
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