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Article summary:
1. This article discusses several classes of stochastic models for the origin times and magnitudes of earthquakes.
2. The models are compared for a Japanese data set for the years 1885–1980 using likelihood methods.
3. Conventional graphical methods associated with stationary Poisson processes can be used to investigate the deviation of the data from the model, allowing for effective use of residual analysis to find features of the data set that are not captured in the model.
Article analysis:
The article is written by Yosihiko Ogata, an expert in statistical mathematics from Institute of Statistical Mathematics (I.S.M.). This lends credibility to his claims and makes it likely that his research is reliable and trustworthy. The article is well-structured and provides detailed information on various classes of stochastic models for earthquake occurrences, as well as residual analysis techniques used to investigate deviations from these models. Furthermore, it provides evidence from a Japanese dataset collected over a period of 95 years (1885-1980).
The article does not appear to have any biases or one-sided reporting, as it presents both sides equally and does not make any unsupported claims or omit any points of consideration or evidence for its claims made. It also does not contain any promotional content or partiality towards any particular viewpoint or opinion. Additionally, possible risks associated with seismic quiescence are noted in the article, making it clear that further research is needed before drawing conclusions about its utility in predicting major earthquakes.
In conclusion, this article appears to be reliable and trustworthy due to its detailed structure and lack of bias or one-sided reporting.