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

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.

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

scholarly journals A Modified STAP Estimator for Superresolution of Multiple Signals

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Zhongbao Wang ◽  
Junhao Xie ◽  
Zilong Ma ◽  
Taifan Quan
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
Surface Wave ◽  
High Frequency ◽  
Real Data ◽  
Multiple Signals ◽  
First Order ◽  
Wave Radar ◽  
Simulation Results ◽  
Space Time Adaptive Processing

A modified space-time adaptive processing (STAP) estimator is described in this paper. The estimator combines the incremental multiparameter (IMP) algorithm and the existing beam-space preprocessing techniques yielding a computationally cheap algorithm for the superresolution of multiple signals. It is a potential technique for the remote sensing of the ocean currents from the broadened first-order Bragg sea echo spectrum of shipborne high-frequency surface wave radar (HFSWR). Some simulation results and real-data analysis are shown to validate the proposed algorithm.

scholarly journals Inaccuracies in Sneddon's Solution for Elastic Indentation by a Rigid Cone and their Implications for Nanoindentation Data Analysis

1996 ◽  
Vol 436 ◽  
Author(s):  
A. Bolshakov ◽  
G. M. Pharr
Keyword(s):  
Finite Element ◽  
Elastic Modulus ◽  
Data Analysis ◽  
Half Space ◽  
Contact Stiffness ◽  
Elastic Half Space ◽  
Berkovich Indenter ◽  
First Order ◽  
Effective Angle ◽  
First Order Correction

AbstractMethods currently used for analyzing nanoindentation load-displacement data to determine a material's hardness and elastic modulus are based on Sneddon's solution for the indentation of an elastic half-space by a rigid axisymmetric indenter. Although this solution is widely used, no attempts have been made to determine how well it works for conditions of finite deformation, as is the case in most nanoindentation experiments with sharp indenters. Analytical and finite element results are presented which show that corrections to Sneddon's solution are needed if it is to be accurately applied to the case of deformation by a rigid cone. Failure to make the corrections results in an underestimation of the load and contact stiffness and an overestimation of the elastic modulus, with the magnitude of the errors depending on the angle of the indenter and Poisson's ratio of the half-space. For a rigid conical indenter with a half-included tip angle of 70.3°, i.e., the angle giving the same area-to-depth ratio as the Berkovich indenter used commonly in nanoindentation experiments, the underestimation of the load and contact stiffness and overestimation of the elastic modulus may be as large as 13%. It is shown that a simple first order correction can be achieved by redefining the effective angle of the indenter in terms of the elastic constants. Implications for the interpretation of nanoindentation data are discussed.

scholarly journals A novel method for the quantification of interfacial  tomato stresses during transportation

2017 ◽  
Vol 63 (No. 3) ◽  
pp. 128-135 ◽  
Author(s):  
Steyn Wynand Jacobus van der Merwe
Keyword(s):  
Data Analysis ◽  
Shelf Life ◽  
Physiological Effects ◽  
Interfacial Stresses ◽  
First Order ◽  
Road Roughness ◽  
Novel Method ◽  
Alternative Routes ◽  
On Farm

Transportation of tomatoes on farm and market roads causes interfacial stresses of tomatoes due to truck dynamics as affected by road and transportation conditions. These stresses may affect the shelf-life of tomatoes if they are high enough to cause damage to the fruit. This paper describes a novel method for the in situ measurement of the stresses during actual transportation of tomatoes, providing the producer information that can assist in taking decisions regarding the use of alternative routes, maintenance of existing routes or changes in packing to prevent excessive stresses onto tomatoes. The process involves measurement of the stresses using a stress-sensor that is recording the interfacial stresses continuously during transportation. These stresses can be correlated to road conditions (quantified through standard road-roughness statistics) and used to subject tomatoes in laboratory conditions to similar stresses to study shelf-life effects of transportation stresses. The paper focuses on the measurement process and first-order data analysis, and excludes a detailed study on the physiological effects of the measured stresses on tomatoes.

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 Interval Estimation of Random Coefficient Integer-Valued Autoregressive Model Based on Mean Empirical Likelihood Method

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xianghong Xu ◽  
Dehui Wang ◽  
Zhiwen Zhao
Keyword(s):  
Data Analysis ◽  
Empirical Likelihood ◽  
Autoregressive Model ◽  
Interval Estimation ◽  
Real Data ◽  
Confidence Regions ◽  
Random Coefficient ◽  
Likelihood Method ◽  
First Order ◽  
The Mean

In this paper, we study the use of the mean empirical likelihood (MEL) method in a first-order random coefficient integer-valued autoregressive model. The MEL ratio statistic is established, its limiting properties are discussed, and the confidence regions for the parameter of interest are derived. Furthermore, a simulation study is presented to demonstrate the performance of the proposed method. Finally, a real data analysis of dengue fever is performed.

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