Sentences with phrase «upper tail»

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

While these two bars were not clearly directional, our bet went with the bears due to the long upper tail.

The extreme upper tail can behave differently than the center of the distribution, measured by the average or median.

Venerated by the Aztecs and Mayans, whose rulers wore headdresses made out of its long tail feathers, the bird has a bright green body, a red breast, and green upper tail feathers that conceal its tail; in males, these feathers are longer than its body.

Normally, we avoid trading counter-trend, but this pin is showing rejection of a longer - term resistance that you can easily see if you zoom out to a weekly chart, and the pin has good definition with a nice bearish close and protruding upper tail.

> It has been argued recently that the combination of risk aversion and an uncertainty distribution of future temperature change with a heavy upper tail invalidates mainstream economic analyses of climate change policy.

It seems to me that based on the general discussion, most people should agree at least sort of approximately with the «cauchy» in that paper, though maybe increasing the dispersion of that cauchy by 50 % would be less controversial... but either way it's going to give a smaller upper tail than the uniform.

Now if the denominator has the largest variance, that would explain unbounded upper tail.

There are some very good — and intellectually fascinating — reasons for why the climate sensitivity distribution is asymmetric and has a fat upper tail, but they are beyond the present scope.

With increasing temperatures expected in the long term [Karl et al., 2009], continued increases in the extreme upper tails of temperature distribution are likely.

That results in the data maximum likelihoods for direct and indirect aerosol forcing being in the upper tails of the priors, biasing the aerosol forcing estimation to more negative values (and hence biasing ECS estimation to a higher value).

The upper tail is particularly long in studies using diagnostics based on large - scale mean data because separation of the greenhouse gas response from that to aerosols or climate variability is more difficult with such diagnostics (Andronova and Schlesinger, 2001; Gregory et al., 2002a; Knutti et al., 2002, 2003).

The results curve from this tiny percentage of the upper tail of the original «bell curve» is another full «bell curve» where the gifted students tend to score at the 50th percentile or above.

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.

Hedges and Nowell [17] note that «blacks are hugely underrepresented in the upper tails of the achievement distributions, and this underrepresentation does not seem to be decreasing.»

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 worth noting that the 1998/99 El - Nino event pushed the observations about as high into the upper tail of the model projections as they are into the lower tail now.

I have concentrated on the Bayesian inference involved in such studies, since they seem to me in many cases to use inappropriate prior distributions that heavily fatten the upper tail of the estimated PDF for S. I may write a future post concerning that issue, but in this post I want to deal with more basic statistical issues arising in what is, probably, the most important of the Bayesian studies whose PDFs for climate sensitivity were featured in AR4.

Here, I have generated a sample 200000 values from an F (3,200) and calculated both the upper tail probabilities (as done in the program) and the likelihood values using the density function.

(The equilibrium referred to is that of the ocean — it doesn't include very slow changes in polar ice sheets, etc.) Obviously, the upper tail of the estimated distribution for S is important, not just its central value.

Note that since TCR scales linearly with the errors in the estimated scaling factors, estimates do not show a tendency for a long upper tail, as is the case for ECS.

A SUFFICIENT condition for a correct answer then is that the estimated CDF asymptotes towards the true unknown CDF in the lower and upper tails.

This seemingly invites an alternative interpretation: With nearly half of all estimates of sensitivity below the ostensibly - safe «guardrail» of 2 °C, perhaps one could legitimately ignore the upper tail, however fat it gets with increasing uncertainty?

For present purposes, the most crucial aspect of the figure is its asymmetry: It has a «fat» upper tail and a fairly skinny lower tail.

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.