density functions
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2022 ◽  
Author(s):  
Edgardo Cañón-Tapia

ABSTRACT Volcanic activity is ultimately controlled by processes that take place many kilometers beneath the surface of a planet. The deeper processes are unlikely to reach the surface without some degree of modification at shallower levels. Nevertheless, traces of those deeper processes may still be found when examining the final products at the surface. In this work, it is shown that it is possible to gain insights concerning the integrated contribution of deep structures through the study of the spatial distribution of volcanic vents at the surface. The method here described relies on the systematic use of increasing smoothing factors in Gaussian kernel estimations. The sequences of probability density functions thus generated are equivalent to images obtained with an increasing wavelength, which therefore have the power to penetrate deeper below the surface. Although the resolution of this method is much smaller than the resolution provided by seismic or other geophysical surveys, it has the advantages of ease of implementation, extremely low cost, and remote application. Thus, the reported method has great value as a first-order exploration tool to investigate the deep structure of a planet, and it can make important contributions to our understanding of the volcano-tectonic relationship, not only on Earth, but also across the various bodies of the solar system where volcanic activity has been documented.


2022 ◽  
Author(s):  
Christopher B. DuRoss ◽  
et al.

Text S1: Bayesian (OxCal) models for northern Lost River fault zone trench sites. Text S2: Bulk sediment analysis and charcoal identification; Text S3: Luminescence geochronology. Table S1: Description of stratigraphic units at the Sheep Creek trench. Table S2: Description of stratigraphic units at the Arentson Gulch trench. Figure S1: Photomosaics and large-format trench logs for the Sheep Creek trench. Figure S2: Photomosaics and large-format trench logs for the Arentson Gulch trench. Figure S3: Sheep Creek and Arentson Gulch vertical displacement measurements. Figure S4: Fault bend angles along the northern Lost River fault zone. Figure S5: Photographs of the Sheep Creek and Arentson Gulch trench sites. Figure S6: Probability density functions for Lost River fault zone ruptures.


2022 ◽  
Author(s):  
Christopher B. DuRoss ◽  
et al.

Text S1: Bayesian (OxCal) models for northern Lost River fault zone trench sites. Text S2: Bulk sediment analysis and charcoal identification; Text S3: Luminescence geochronology. Table S1: Description of stratigraphic units at the Sheep Creek trench. Table S2: Description of stratigraphic units at the Arentson Gulch trench. Figure S1: Photomosaics and large-format trench logs for the Sheep Creek trench. Figure S2: Photomosaics and large-format trench logs for the Arentson Gulch trench. Figure S3: Sheep Creek and Arentson Gulch vertical displacement measurements. Figure S4: Fault bend angles along the northern Lost River fault zone. Figure S5: Photographs of the Sheep Creek and Arentson Gulch trench sites. Figure S6: Probability density functions for Lost River fault zone ruptures.


2022 ◽  
Vol 7 ◽  
pp. e6803
Author(s):  
Iuliia Pinkovetskaia

Study was devoted to the assessment of indicators characterizing the number and structure of research and teaching staff at universities and other institutions of higher education in the regions of Russia. These indicators were the number of teachers working in higher education, per thousand residents and per hundred students, proportion of professors and associate professors in the whole number of teachers. Research used official statistical information for 82 regions of Russia. We used density functions of normal distribution as models. Study showed that on average, there was a little more than one teacher working in higher education organizations per thousand residents. It is proved that on average, every seventh teacher in all regions held the position of professor. Approximately two-thirds of all teachers held associate professor positions, there were five teachers per one hundred students.


2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Ryszard SNOPKOWSKI ◽  
Marta SUKIENNIK ◽  
Aneta NAPIERAJ

The article presents selected issues in the field of stochastic simulation of production process-es. Attention was drawn to the possibilityof including, in this type of models, the risk accompanying the implementation of processes. Probability density functions that can beused to characterize random variables present in the model are presented. The possibility of making mistakes while creat-ing this typeof models was pointed out. Two selected examples of the use of stochastic simulation in the analysis of production processes on theexample of the mining process are presented.


Radiocarbon ◽  
2021 ◽  
pp. 1-22
Author(s):  
Nicholas V Kessler

ABSTRACT Age disparities between charcoal samples and their context are a well-known problem in archaeological chronometry, and even small offsets could affect the accuracy of high-precision wiggle-matched dates. In many cases of taphonomic or anthropogenic loss of the outermost rings, sapwood-based methods for estimating cutting dates are not always applicable, especially with charcoal. In these instances, wiggle-matched terminus post quem (TPQ) dates are often reconciled with subjective or ad hoc approaches. This study examines the distribution of age disparities caused by ring loss and other factors in a large dendroarchaeological dataset. Probability density functions describing the random distribution of age disparities are then fit to the empirical distributions. These functions are tested on an actual wiggle-matched non-cutting date from the literature to evaluate accuracy in a single case. Simulations are then presented to demonstrate how an age offset function can be applied in OxCal outlier models to yield accurate dating in archaeological sequences with short intervals between dated episodes, even if all samples are non-cutting dates.


Author(s):  
Kunio Takezawa

When data are found to be realizations of a specific distribution, constructing the probability density function based on this distribution may not lead to the best prediction result. In this study, numerical simulations are conducted using data that follow a normal distribution, and we examine whether probability density functions that have shapes different from that of the normal distribution can yield larger log-likelihoods than the normal distribution in the light of future data. The results indicate that fitting realizations of the normal distribution to a different probability density function produces better results from the perspective of predictive ability. Similarly, a set of simulations using the exponential distribution shows that better predictions are obtained when the corresponding realizations are fitted to a probability density function that is slightly different from the exponential distribution. These observations demonstrate that when the form of the probability density function that generates the data is known, the use of another form of the probability density function may achieve more desirable results from the standpoint of prediction.


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