scholarly journals Mechanisms for log normal concentration distributions in the environment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
August Andersson
Keyword(s):  
Data Analysis ◽  
Normal Concentration ◽  
First Order ◽  
Log Normal ◽  
Frequent Observation ◽  
Source And Sink

AbstractLog normal-like concentration distributions are ubiquitously observed in the environment. However, the mechanistic origins are not well understood. In this paper, we show that first order exponential kinetics onsets log-normal concentration distributions, under certain assumptions. Given the ubiquity of exponential kinetics, e.g., source and sink processes, this model suggests an explanation for the frequent observation in the environment, and elsewhere. We compare this model to other mechanisms affecting concentration distributions, e.g., source mixing. Finally, we discuss possible implications for data analysis and modelling, e.g., log-normal rates and fluxes.

scholarly journals On the Use of Entropy Issues to Evaluate and Control the Transients in Some Epidemic Models

Entropy ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. 534 ◽  
Author(s):  
Manuel De la Sen ◽  
Raul Nistal ◽  
Asier Ibeas ◽  
Aitor J. Garrido
Keyword(s):  
Differential Equation ◽  
Ad Hoc ◽  
Equilibrium Points ◽  
Time Instant ◽  
Equation Model ◽  
Epidemic Models ◽  
Time Varying ◽  
Feedback Information ◽  
First Order ◽  
Log Normal

This paper studies the representation of a general epidemic model by means of a first-order differential equation with a time-varying log-normal type coefficient. Then the generalization of the first-order differential system to epidemic models with more subpopulations is focused on by introducing the inter-subpopulations dynamics couplings and the control interventions information through the mentioned time-varying coefficient which drives the basic differential equation model. It is considered a relevant tool the control intervention of the infection along its transient to fight more efficiently against a potential initial exploding transmission. The study is based on the fact that the disease-free and endemic equilibrium points and their stability properties depend on the concrete parameterization while they admit a certain design monitoring by the choice of the control and treatment gains and the use of feedback information in the corresponding control interventions. Therefore, special attention is paid to the evolution transients of the infection curve, rather than to the equilibrium points, in terms of the time instants of its first relative maximum towards its previous inflection time instant. Such relevant time instants are evaluated via the calculation of an “ad hoc” Shannon’s entropy. Analytical and numerical examples are included in the study in order to evaluate the study and its conclusions.

scholarly journals The Nested_fit Data Analysis Program

Proceedings ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 14 ◽  
Author(s):  
Martino Trassinelli
Keyword(s):  
Data Analysis ◽  
Probability Distributions ◽  
Analysis Program ◽  
Large Database ◽  
Data Set ◽  
Lawn Mower ◽  
Bayesian Data Analysis ◽  
Bayesian Evidence ◽  
Spectral Profiles ◽  
Log Normal

We present here Nested_fit, a Bayesian data analysis code developed for investigations of atomic spectra and other physical data. It is based on the nested sampling algorithm with the implementation of an upgraded lawn mower robot method for finding new live points. For a given data set and a chosen model, the program provides the Bayesian evidence, for the comparison of different hypotheses/models, and the different parameter probability distributions. A large database of spectral profiles is already available (Gaussian, Lorentz, Voigt, Log-normal, etc.) and additional ones can easily added. It is written in Fortran, for an optimized parallel computation, and it is accompanied by a Python library for the results visualization.

Estimation of log-normal quantiles: Monte Carlo results and first-order approximations

1984 ◽  
Vol 71 (1-2) ◽  
pp. 1-30 ◽  
Author(s):  
Kiyoshi Hoshi ◽  
Jery R Stedinger ◽  
Stephen J Burges
Keyword(s):  
Monte Carlo ◽  
First Order ◽  
Log Normal

scholarly journals Did an Ebola outbreak influence the 2014 U.S. federal elections? (Hint: Only if you ignore autocorrelation)

2016 ◽  
Author(s):  
Leonid Tiokhin ◽  
Daniel Hruschka
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Online Search ◽  
First Order ◽  
Search Volume ◽  
Temporal Autocorrelation ◽  
Analytical Strategies ◽  
Existing Data

In a recent paper, Beall, Hofer, and Schaller (2016) use observational time series data to test the hypothesis that the 2014 Ebola outbreak influenced the 2014 U.S. Federal Elections. They find substantial associations between online search volume for Ebola and people’s tendency to vote Republican, an effect observed primarily in states with norms favoring Republican candidates. However, the analyses do not deal with the well-known problem of temporal autocorrelation in time series. We show that all variables analyzed exhibit extremely high levels of temporal autocorrelation (i.e. similarity in data-point values across time). After appropriately removing first-order autocorrelation, the observed relationships are attenuated and non-significant. This suggests that either no real associations exist, or that existing data are insufficiently powered to test the proposed hypotheses. We conclude by highlighting other pitfalls of observational data analysis, and draw attention to analytical strategies developed in related disciplines for avoiding these errors.

scholarly journals Did an Ebola outbreak influence the 2014 U.S. federal elections? (Hint: Only if you ignore autocorrelation)

2016 ◽  
Author(s):  
Leonid Tiokhin ◽  
Daniel Hruschka
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Online Search ◽  
First Order ◽  
Search Volume ◽  
Temporal Autocorrelation ◽  
Analytical Strategies ◽  
Existing Data

In a recent paper, Beall, Hofer, and Schaller (2016) use observational time series data to test the hypothesis that the 2014 Ebola outbreak influenced the 2014 U.S. Federal Elections. They find substantial associations between online search volume for Ebola and people’s tendency to vote Republican, an effect observed primarily in states with norms favoring Republican candidates. However, the analyses do not deal with the well-known problem of temporal autocorrelation in time series. We show that all variables analyzed exhibit extremely high levels of temporal autocorrelation (i.e. similarity in data-point values across time). After appropriately removing first-order autocorrelation, the observed relationships are attenuated and non-significant. This suggests that either no real associations exist, or that existing data are insufficiently powered to test the proposed hypotheses. We conclude by highlighting other pitfalls of observational data analysis, and draw attention to analytical strategies developed in related disciplines for avoiding these errors.

scholarly journals Penerapan Konsep Persamaan Diferensial Biasa Pada Pemodelan Tali Penahan Jembatan Gantung

2021 ◽  
Vol 1 (4) ◽  
pp. 559-569
Author(s):  
Sri Wulandari Pratiwi ◽  
Arjudin Arjudin ◽  
Nani Kurniati ◽  
Sripatmi Sripatmi
Keyword(s):  
Data Analysis ◽  
Differential Equations ◽  
Ordinary Differential Equations ◽  
Quantitative Research ◽  
Suspension Bridge ◽  
Suspension Bridges ◽  
First Order ◽  
Independent Variable ◽  
The Subject ◽  
Development Methods

bridge from the concept of ordinary differential equations and to determine solving differential equations and capitalizing suspension bridges, with the suspension bridge in Gerung, West Lombok is a modeling. The type of this research is Quantitative research with development methods literature. The subject in this research retaining ropes on suspension bridges. The data collected in the form of journals or articles from various related sources model of the retaining rope on a computed suspension bridge analyzed and concluded by the researcher through data analysis techniques by using the type of research triangulation principle and theoretical triangulation based on the results of data analysis, it was found that differential equations can be applied to modeling suspension bridges through first-order ordinary differential equations with the form of capitalization equations with the solution , with the interval in . The Gerung suspension bridge has its retaining rope modeling solution is , in 12 right suspensions at each hose in the interval the related variable is the height of the retaining rope and x the independent variable is the distance from the lowest restraint to the rope to be measured.

Dispersive first-order reactions. I. Data analysis

1994 ◽  
Vol 182 (1) ◽  
pp. 53-59 ◽  
Author(s):  
H. Schäfer ◽  
U. Albrecht ◽  
R. Richert
Keyword(s):  
Data Analysis ◽  
First Order

Methods for kinetic analysis of simultaneous, first-order reactions in waters: The kinetic model and methods for data analysis

1994 ◽  
Vol 288 (3) ◽  
pp. 131-139 ◽  
Author(s):  
Yanjia Lu ◽  
C.L. Chakrabarti ◽  
M.H. Back ◽  
D.C. Grégoire ◽  
W.H. Schroeder ◽  
...  
Keyword(s):  
Data Analysis ◽  
Kinetic Model ◽  
Kinetic Analysis ◽  
First Order
Sign in / Sign up

Export Citation Format

Share Document