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Question

[...] contend that the goal of probabilistic forecasting is to maximize the sharpness of the predictive distributions subject to calibration.

Answer

Gneiting et al. (2007)

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Gneiting, Balabdaoui, and Raftery (2007) contend that the goal of probabilistic forecasting is to maximize the sharpness of the predictive distributions subject to calibration.

Question

In the case of count data, the predictive distribution is discrete which means the PIT [...] under the hypothesis of an ideal forecast

Answer

is no longer uniform

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In the case of count data, the predictive distribution is discrete which means the PIT is no longer uniform under the hypothesis of an ideal forecast

Famous Examples of Naru Literature

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simply removing a lawless usurper who had no claim to rule. Whether Darius I was telling the truth is of no consequence because his reign was so effective and impressive it legitimized itself. <span>Famous Examples of Naru Literature Other pieces of Naru literature from the 2nd millennium BCE, such as those concerning Naram-Sin, made clear the role of the gods in people's lives and how one should behave in dealing w

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pieces of Naru literature from the 2nd millennium BCE, such as those concerning Naram-Sin, made clear the role of the gods in people's lives and how one should behave in dealing with divinity. <span>The work known as The Great Revolt, a kind of historical fiction, makes use of the historical rebellions against Naram-Sin's early rule but then embellish on the facts in order to impress upon an audience the military brilliance of Naram-Sin and the ungrateful nature of the city of Kish, which organized the rebellion against him. In the Legend of Cutha (also known as the Cutha Legend and the Kutha Legend), also from the 2nd millennium BCE, the importance of listening to, and obeying, the will of the gods is the

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ogical concern for the right relationship between the gods and the absolute monarch" (Leick, 107), whose author chose Akkad and Naram-Sin as subjects because, by that time, they were legendary. <span>According to the historical evidence, Naram-Sin honored the gods and was very pious. What the historical king may have been like, and what he did, was of no consequence to the author of The Curse of Agade; what mattered was the moral of the story, and historical truths that did not fit that story were of no importance. Conclusion Again, as mentioned above, to a modern reader such a practice may be interpreted as dishonest but, to an ancient hearer of the tale, the story's message was important, not th

Again, as mentioned above, to a modern reader such a practice may be interpreted as dishonest but, to an ancient hearer of the tale, the story's message was important, not the "facts" contained therein. Plato discusses this in his work *Republic*, Book II, when he is addressing the concept of the True Lie (also known as the Lie in the Soul). In discussing various kinds of untruths, he has the character of Socrates say:

Whereas the lie in words is in certain cases useful and not hateful; in dealing with enemies – that would be an instance; or again, when those whom we call our friends in a fit of madness or illusion are going to do some harm, then it is useful and is a sort of medicine or preventative; also in the tales of mythology, of which we were just now speaking – because we do not know the truth about ancient times, we make falsehood as much like truth as we can, and so turn it to account. (378-382d)

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he did, was of no consequence to the author of The Curse of Agade; what mattered was the moral of the story, and historical truths that did not fit that story were of no importance. Conclusion <span>Again, as mentioned above, to a modern reader such a practice may be interpreted as dishonest but, to an ancient hearer of the tale, the story's message was important, not the "facts" contained therein. Plato discusses this in his work Republic, Book II, when he is addressing the concept of the True Lie (also known as the Lie in the Soul). In discussing various kinds of untruths, he has the character of Socrates say: Whereas the lie in words is in certain cases useful and not hateful; in dealing with enemies – that would be an instance; or again, when those whom we call our friends in a fit of madness or illusion are going to do some harm, then it is useful and is a sort of medicine or preventative; also in the tales of mythology , of which we were just now speaking – because we do not know the truth about ancient times, we make falsehood as much like truth as we can, and so turn it to account. (378-382d) Mythology has always explained to human beings how the world works, where people came from, why they are here, and mythology has always been accepted by those hearing the tales, either

SMC: With increasing dimensionality of the target distribution, however, the weights degenerate

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With increasing dimensionality of the target distribution, however, the weights degenerate: a small number of particles are assigned relatively large weights and most of the particles have weight zero. To overcome weight degeneracy, resampling steps can be inserted in order t

SDEs are much easier to solve numerically than the Kolmogorov differential equations

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the SDEs are much easier to solve numerically than the Kolmogorov differential equations and faster than simulating sample paths of the CTMC model

SDEs are much faster to solve numerically than simulating sample paths of the CTMC model

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the SDEs are much easier to solve numerically than the Kolmogorov differential equations and faster than simulating sample paths of the CTMC model

Question

More realistic distributions for the length of [...] can be obtained by choosing p(t) to be a gamma probability density function [22–27]

Answer

the infectious period

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More realistic distributions for the length of the infectious period can be obtained by choosing p(t) to be a gamma probability density function [22–27]

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> The branching process approximation is a CTMC, but near the disease-free equilibrium, the rates are linear (Table 2). Three important assumptions underlie the branching process approximation: <span>Each infectious individual behavior is independent from other infectious individuals. Reasonable if a small number of infectious individuals is introduced into a large homogeneously-mixed population (assumption (3)). Each infectious individual has the same probability of recovery and the same probability of transmitting an infection. Reasonable in a homogeneously-mixed population with constant trans

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ual behavior is independent from other infectious individuals. Reasonable if a small number of infectious individuals is introduced into a large homogeneously-mixed population (assumption (3)). <span>Each infectious individual has the same probability of recovery and the same probability of transmitting an infection. Reasonable in a homogeneously-mixed population with constant transmission and recovery rates, b and g. The susceptible population is sufﬁciently large. <span>

Branching process assumption: The susceptible population is sufﬁciently large.

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as the same probability of recovery and the same probability of transmitting an infection. Reasonable in a homogeneously-mixed population with constant transmission and recovery rates, b and g. <span>The susceptible population is sufﬁciently large. <span>

Tags

#reading

Question

If T is a statistic then T = t(X) is [...] and t = t(x) the corresponding value of the random variable when X = x.

Answer

a random variable

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If T is a statistic then T = t(X) is a random variable and t = t(x) the corresponding value of the random variable when X = x.

Tags

#reading

Question

If T is a statistic then T = t(X) is a random variable and t = t(x) [...].

Answer

the corresponding value of the random variable when X = x

status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
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repetition number in this series | 0 | memorised on | scheduled repetition | ||||

scheduled repetition interval | last repetition or drill |

If T is a statistic then T = t(X) is a random variable and t = t(x) the corresponding value of the random variable when X = x.