Sentences with phrase «prediction intervals»

Something to do with prediction intervals for the proxy data (1961 - 1994, withheld from calibration)?
The solid black line is the least - squares fitted line and the blue lines indicate 95 percent prediction intervals for temperature using this linear relationship.
Even a low CE value may still provide prediction intervals that are useful for drawing particular scientific conclusions.
The figure also illustrates predictions made at proxy values A and B and the corresponding prediction intervals (wide blue lines) for the temperature.
We have different central forecasts and different levels of uncertainty, but we all agree that there is a lot of uncertainty, with prediction intervals (ranges of reasonably probable outcomes) varying from + / - 25 to + / -45 seats.
Similarly, the Labour prediction interval suggests it is extremely unlikely that Ed Miliband will do as well as Tony Blair in 1997 or 2001 but it would not be surprising (given polling in previous elections) if he did worse than Gordon Brown or Michael Foot.
Although some debate has focused on when a validation statistic, such as CE or RE, is significant, a more meaningful approach may be to concentrate on the implied prediction intervals for a given reconstruction.
On the basis of these assumptions and an approximate Gaussian distribution for the noise in the relationship between temperature and the proxies, one can derive prediction intervals for the reconstructed temperatures using standard techniques (see, e.g., Draper and Smith 1981).
The curved blue lines in Figure 9 - 1 present the calibration error, or the uncertainty in predictions based on the calibration (technically the 95 percent prediction interval, which has probability 0.95 of covering the unknown temperature), which is a standard component of a regression analysis.
These prediction intervals are not just niceties but need to be taken seriously.
At first glance these prediction intervals may seem to encompass all foreseeable outcomes and more.
The second of the two most striking features is that the prediction intervals for shares of the vote are enormous.
These include methods «that emphasize estimation over testing such as confidence, credibility, or prediction intervals; Bayesian methods; alternative measures of evidence such as likelihood ratios or Bayes factors; and other approaches such as decision - theoretic modeling and false discovery rates.»
I have found that such groupings extend the prediction interval to (roughly) the length of the group.
As long as the observed trajectory lies within the prediction interval, it is not inconsistent with our understanding as formalized in the models.
You would not compare that measurement with the mean height of Dutch people or even the confidence interval on that mean (which gets vanishingly narrow with a large sample size), you would compare it with the overall spread of the height distribution in that country: the prediction interval.
So, the proper comparison is not the observed trend with the mean, it is with the range of trajectories produced by the model ensemble — that prediction interval is what the scatter of squiggles in fig. 2 shows.
If it is within the prediction interval, you can conclude that the person's height is not inconsistent with their being Dutch.
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