Sentences with phrase «tails of the distribution»

My goal was to chop off the left tail of the distribution of returns.

This is not necessarily a contradiction, because 5,000 + square foot homes are relatively uncommon and represent the extreme upper tail of the distribution.

The pace of increases in mean BMI was slower than that of the prevalence, suggesting that more of the increase is attributable to the upper tail of the distribution.

The answer is in fact explicitly stated in Hansen's PNAS in the first place: «In addition, the distribution has broadened, the shift being greater at the high temperature tail of the distribution.»

They also demonstrated that the extreme events which make up the heavy tails of the distribution of the Euro Stoxx 50 logarithmic graph of financial returns distort the scaling in the data set.

They found that dissipation followed what's known as a lognormal distribution — one in which one tail of the distribution dominates the average.

Rebalancing is about minimizing risk — looking at the left - sided tail of the distribution.

The cats and dogs in the long tail of the distribution deserve further analysis, since understanding what features are predictive of a long wait for a new home might lead to new strategies for accelerating their adoptions.

But given that Lewis» numbers are about a third lower, and the fat right - hand tail of the distribution is enormously lower - why wouldn't that matter a tremendous lot?

In grades 9 — 10, the magnitude of the coefficients is the largest for students in the 25th percentile, and slowly decreases as one moves toward the upper tail of the distribution.

In addition, the distribution has broadened, the shift being greater at the high temperature tail of the distribution.»

That is because the long tail of the distribution is dominated by people whose salient feature is that nobody knows who they are.

That would tend to spread the tails of the distribution nsuch that the mean is higher than the other measures of central tendency.

When we look at traditional diets, we have to be careful of emulating the tails of the distribution.

Importantly, valuation mattered in both tails of the distribution.

This aspect also matters for extreme events which always involve small statistical samples (by definition — tails of the distribution) and therefore we should expect to see patchy and noisy maps due to random sampling fluctuations.

The flap about sea level is a reminder that I.P.C.C. doesn't work well on topics that are outside the normal bounds of consensus science — yet those «extremes» are key to understanding the tails of the distributions, especially those that relate to possible catastrophic changes in climate systems.

Since cost probably increases quite super-linearly with temperature, it is possible that the tails of the distribution could dominate risk even though they are quite improbable.

Our results reveal a marked increase in the probability of a 30 - day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9 - 18 % today (depending on the region) to 30 - 40 % at the upper tail of the distribution.

It is vital that as a community we focus more attention on detecting changes in the tails of the distributions of weather events.

If the problem is generalized to look at the entire probability distribution function (pdf) of the climate variables, then the biggest changes percentagewise occur in the tails of the distribution, where they can easily exceed several hundred percent (Trenberth 2011b).

To be useful in a risk context, climate change assessments therefore need a much more thorough exploration of the tails of the distributions of physical variables such as sea level rise, temperature, and precipitation, where our scientific knowledge base is less complete, and where sophisticated climate models are less helpful.

Do we not have a professional obligation to talk about the whole probability distribution, given the tough consequences at the tail of the distribution?

But when the tails of the distribution are fat (i.e., when they fall off a lot more slowly than exp -LRB-- x ^ 2), and especially if they fall off only polynomially) then the expected cost of the risk is dominated by the extreme of the low - probablity / high - risk tail.

Thus, they only exclude the most extreme emissions scenarios found in the literature - those situated in the tails of the distribution.