Statistical sightings of better angels: Analysing the distribution of battle-deaths in interstate conflict over time

Have great wars become less violent over time, and is there something we might identify as the long peace? We investigate statistical versions of such questions, by examining the number of battle-deaths in the Correlates of War dataset, with 95 interstate wars from 1816 to 2007. Previous research has found this series of wars to be stationary, with no apparent change over time. We develop a framework to find and assess a change-point in this battle-deaths series. Our change-point methodology takes into consideration the power law distribution of the data, models the full battle-deaths distribution, as opposed to focusing merely on the extreme tail, and evaluates the uncertainty in the estimation. Using this framework, we find evidence that the series has not been as stationary as past research has indicated. Our statistical sightings of better angels indicate that 1950 represents the most likely change-point in the battle-deaths series – the point in time where the battle-deaths distribution might have changed for the better.

Download Full-text

Quantitative analysis of cryptocurrencies transaction graph

Applied Network Science ◽

10.1007/s41109-019-0249-6 ◽

2019 ◽

Vol 4 (1) ◽

Cited By ~ 4

Author(s):

Amir Pasha Motamed ◽

Behnam Bahrak

Keyword(s):

Growth Rate ◽

Statistical Analysis ◽

Quantitative Analysis ◽

Power Law ◽

Degree Sequence ◽

Power Law Distribution ◽

Comprehensive Comparison ◽

Statistical Studies ◽

Financial Transactions ◽

Over Time

AbstractCryptocurrencies as a new way of transferring assets and securing financial transactions have gained popularity in recent years. Transactions in cryptocurrencies are publicly available, hence, statistical studies on different aspects of these currencies are possible. However, previous statistical analysis on cryptocurrencies transactions have been very limited and mostly devoted to Bitcoin, with no comprehensive comparison between these currencies. In this study, we intend to compare the transaction graph of Bitcoin, Ethereum, Litecoin, Dash, and Z-Cash, with respect to the dynamics of their transaction graphs over time, and discuss their properties. In particular, we observed that the growth rate of the nodes and edges of the transaction graphs, and the density of these graphs, are closely related to the price of these currencies. We also found that the transaction graph of these currencies is non-assortative, i.e. addresses do not tend for transact with a particular type of addresses of higher or lower degree, and the degree sequence of their transaction graph follows the power law distribution.

Download Full-text

A dynamic power-law sexual network model of gonorrhoea outbreaks

10.1101/322875 ◽

2018 ◽

Author(s):

Lilith K Whittles ◽

Peter J White ◽

Xavier Didelot

Keyword(s):

Network Model ◽

Power Law ◽

Dynamic Network ◽

Great Promise ◽

Model Parameters ◽

Power Law Distribution ◽

Time Model ◽

Dynamic Network Model ◽

The Impact ◽

Over Time

AbstractHuman networks of sexual contacts are dynamic by nature, with partnerships forming and breaking continuously over time. Sexual behaviours are also highly heterogeneous, so that the number of partners reported by individuals over a given period of time is typically distributed as a power-law. Both the dynamism and heterogeneity of sexual partnerships are likely to have an effect in the patterns of spread of sexually transmitted diseases. To represent these two fundamental properties of sexual networks, we developed a stochastic process of dynamic partnership formation and dissolution, which results in power-law numbers of partners over time. Model parameters can be set to produce realistic conditions in terms of the exponent of the power-law distribution, of the number of individuals without relationships and of the average duration of relationships. Using an outbreak of antibiotic resistant gonorrhoea amongst men have sex with men as a case study, we show that our realistic dynamic network exhibits different properties compared to the frequently used static networks or homogeneous mixing models. We also consider an approximation to our dynamic network model in terms of a much simpler branching process. We estimate the parameters of the generation time distribution and offspring distribution which can be used for example in the context of outbreak reconstruction based on genomic data. Finally, we investigate the impact of a range of interventions against gonorrhoea, including increased condom use, more frequent screening and immunisation, concluding that the latter shows great promise to reduce the burden of gonorrhoea, even if the vaccine was only partially effective or applied to only a random subset of the population.

Download Full-text

Extra Version and Neuroticism in Team Sport Participants, Individual Sport Participants, and Nonparticipants

Perceptual and Motor Skills ◽

10.2466/pms.105.1.265-275 ◽

2007 ◽

Vol 105 (1) ◽

pp. 265-275 ◽

Cited By ~ 11

Author(s):

Jessica R. Eagleton ◽

Stuart J. McKelvie ◽

Anton De Man

Keyword(s):

Test Scores ◽

Biological Theory ◽

Sport Participation ◽

Past Research ◽

Team Sport ◽

First Year ◽

Change Over Time ◽

Personality Differences ◽

Eysenck Personality Inventory ◽

Over Time

Scores on Extraversion and on Neuroticism as measured by the Eysenck Personality Inventory were compared for 90 undergraduate team sport participants, individual sport participants, and nonparticipants (43 men, 47 women, M age = 20.3 yr.). From past research and Eysenck's biological theory of personality, it was hypothesized that sport participants would score higher on Extraversion and lower on Neuroticism than nonparticipants, and that team participants would score higher on Extraversion and perhaps higher on Neuroticism than individual sport participants. By comparing scores for students in first year and final year, it was also investigated whether pre-existing personality differences drew people to sport (the gravitational hypothesis) or whether personality changed as a function of sport participation (the developmental hypothesis). The main findings were that team participants scored higher on Extraversion than both individual sport participants and nonparticipants, and that test scores did not change over time, supporting the gravitational hypothesis for Extraversion.

Download Full-text

Inspecting gradual and abrupt changes in emotion dynamics with the time-varying change point autoregressive model

10.31234/osf.io/7j6dn ◽

2020 ◽

Author(s):

Casper J Albers ◽

Laura Francina Bringmann

Keyword(s):

Negative Affect ◽

Positive Affect ◽

Change Point ◽

A Priori ◽

Ar Model ◽

Time Varying ◽

Change Over Time ◽

Abrupt Changes ◽

Emotion Dynamics ◽

Over Time

Recent studies have shown that emotion dynamics such as inertia (i.e., autocorrelation) can change over time. Importantly, current methods can only detect either gradual or abrupt changes in inertia. This means that researchers have to choose a priori whether they expect the change in inertia to be gradual or abrupt. This will leave researchers in the dark regarding when and how the change in inertia occurred. Therefore in this article we use a new model: the time-varying change point autoregressive (TVCP-AR) model. The TVCP-AR model can detect both gradual and abrupt changes in emotion dynamics. More specifically, we show that the inertia of positive affect and negative affect measured in one individual differ qualitativelyin how they change over time. Whereas the inertia of positive affect increased only gradually over time, negative affect changed both in a gradual and abrupt fashion over time. This illustrates the necessity of being able to model both gradual and abrupt changes in order to detect meaningful quantitative and qualitative differences in temporal emotion dynamics.

Download Full-text