回复：关于某人《马克西姆_云定律科学骗术真相》一文的解答

大家请看下图，图中红线是用古登堡里克特定律在长时间尺度拟合数据获得的一个b值，对于同一区域，如果我们用古登堡里克特定律拟合不同时间段的地震数据，我们会得到不同的b值，见图中的b1，b2，b3，b4等等，长期观测可以发现，这些b值是围绕长时间尺度获得的b值变化的。那么一个问题就是，根据这些短时间尺度获得的b值相对于长时间尺度b值的差异可以判断大地震的趋势吗？我细想后觉得这恐怕不行，大家也想想。

如下图所示是某个区域一个长时间尺度地震的次数随地震级数的变化，红线是古登堡里克特定律对这些数据的拟合，斜率是b。注意这里的N不含任何时间信息，不同时间的地震数据按级数大小分布在图中。
现在让我们假定，对某个短时间段（第一时间段）的数据进行GR拟合获得个斜率比b小的b1值，但这个时间段地震的次数总体比预期（红线）要低；对另一个时间段（第二时间段）的数据进行拟合，得到的斜率b2比b大得多，地震次数总体也比预期（红线）的要大；第三时间段获得的b3也比b大，但期间的地震次数偏低；第四时间段获得的b4比b小，但地震次数偏多。那么问题是，b1 ,b2，b3，b4都与长时间尺度获得的b值有偏离，或大或小，难道它们都能是地震的前兆吗？
我的观点是，在第二和第四时间段的b值偏离不能作为前兆，因为此时地震的次数已经超出了平均值，不管所得b值怎么偏离，其后大地震的发生都应是小概率事件。图中第一时间段和第三时间段地震次数相比预期偏少，所以不论b值偏大还是偏小，随后发生大地震的可能性都是很高的。即使b值与长时间尺度b值相同，如果地震次数偏少，仍然说明发生大地震的可能性很大。可见，在上述四种情况下，b值相对的偏离不能作为地震前兆指标来使用，此时，地震次数的偏离更能作为签字指标使用。所以可以认为，b值偏离能够作为前兆指标使用的先决条件应该是地震次数没有偏离或偏离不大，此时b值越大，发生大地震的可能性越高；b值越小，发生小地震的可能性就越大。
以上分析供研究人员参考。
古登堡里克特定律并不含有地震的时间信息（不要被无知的山水如屏瞎话蒙蔽），通过应用马克西姆_云定律，我们可以利用不同时间段GR拟合参数相对于长时间尺度GR参数的偏离来判定地震趋势，但即使这样，从上面的分析我们可以看到，如何由GR参数偏离来判定地震趋势仍非常复杂，远不如直接使用马克西姆_云定律进行地震判定来的直接便利。

说某单位一年里总共引进了365位员工，平均每天引进1人。山水如屏这夯货发表意见了，说可以肯定，这个单位引进人员的数目是随时间变化的，也就是每天引进1人。。。他能把平均每天的量理解为每天的实际量。这是北大的才子？我看蠢材差不多

估计地震局人员80%没经历过地震，像山水如屏这种坐办公室写稿子的，估计遇到地震就尿裤子

据报道，从汶川地震到九寨沟地震，10年间地震研究无实质性进展

其实不然，2016年马克西姆_云定律的横空出世，为地震研究撒下了一片曙光

楼主，你的确素好银捏

下图是华北地区6级以上地震数据，从哪里看到不遵从线性规律？。

牵涉到定律、假说和经验公式（或经验关系），大家学习一下：
The laws of science, scientific laws, or scientific principles are statements that describe or predict a range of phenomena as they appear in nature. The term "law" has diverse usage inmany cases: approximate, accurate, broad or narrow theories, in all natural scientific disciplines (physics, chemistry, biology, geology, astronomy etc.).
Scientific laws summarize and explain a large collection of facts determined by experiment, and are tested based on their ability to predict the results of future experiments. They are developed either from facts or through mathematics, and are strongly supported by empirical evidence. It is generally understood that they reflect causal relationships fundamental to reality, and are discovered rather than invented.

Laws reflect scientific knowledge that experiments have repeatedly verified (and never falsified). Their accuracy does not change when new theories are worked out, but rather the scope of application, since the equation (if any) representing the law does not change. As with other scientific knowledge, they do not have absolute certainty (as mathematical theorems or identities do), and it is always possible for a law to be overturned by future observations. A law can usually be formulated as one or several statements or equations, so that it can be used to predict the outcome of an experiment, given the circumstances of the processes taking place.

Laws differ from hypotheses and postulates, which are proposed during the scientific process before and during validation by experiment and observation. These are not laws since they have not been verified to the same degree and may not be sufficiently general, although they may lead to the formulation of laws. A law is a more solidified and formal statement, distilled from repeated experiment. Laws are narrower in scope than scientific theories, which may contain one or several laws. Unlike hypotheses, theories and laws may be simply referred to as scientific fact.Although the nature of a scientific law is a question in philosophy and although scientific laws describe nature mathematically, scientific laws are practical conclusions reached by the scientific method; they are intended to be neither laden with ontological commitments nor statements of logical absolutes.

According to the unity of science thesis, all scientific laws follow fundamentally from physics. Laws which occur in other sciences ultimately follow from physical laws. Often, from mathematically fundamental viewpoints, universal constants emerge from scientific laws.

In science, an empirical relationship or phenomenological relationship is a relationship or correlation that is supported by experiment and observation but not necessarily supported by theory.

An empirical relationship is supported by confirmatory data irrespective of theoretical basis such as first principles. Sometimes theoretical explanations for what were initially empirical relationships are found, in which case the relationships are no longer considered empirical. An example was the Rydberg formula to predict the wavelengths of hydrogen spectral lines. Proposed in 1876, it perfectly predicted the wavelengths of the Lyman series, but lacked a theoretical basis until Niels Bohr produced his Boh rmodel of the atom in 1925.
On occasion, what was thought to be an empirical factor is later deemed to be a fundamental physical constant.

Some empirical relationships are merely approximations, often equivalent to the first few terms of the Taylor series of the analytical solution describing the phenomenon. Other relationships only hold under certain specific conditions, reducing them to special cases of more general relationship. Some approximations, in particular phenomenological models, may even contradict theory; they are employed because they are more mathematically tractable than some theories, and are able to yield results.