scholarly journals Is this scaling nonlinear?

2016 ◽  
Vol 3 (7) ◽  
pp. 150649 ◽  
Author(s):  
J. C. Leitão ◽  
J. M. Miotto ◽  
M. Gerlach ◽  
E. G. Altmann
Keyword(s):  
Complex Systems ◽  
Confidence Intervals ◽  
Probabilistic Framework ◽  
Heavy Tailed ◽  
The City

One of the most celebrated findings in complex systems in the last decade is that different indexes y (e.g. patents) scale nonlinearly with the population x of the cities in which they appear, i.e. y ∼ x β , β ≠1. More recently, the generality of this finding has been questioned in studies that used new databases and different definitions of city boundaries. In this paper, we investigate the existence of nonlinear scaling, using a probabilistic framework in which fluctuations are accounted for explicitly. In particular, we show that this allows not only to (i) estimate β and confidence intervals, but also to (ii) quantify the evidence in favour of β ≠1 and (iii) test the hypothesis that the observations are compatible with the nonlinear scaling. We employ this framework to compare five different models to 15 different datasets and we find that the answers to points (i)–(iii) crucially depend on the fluctuations contained in the data, on how they are modelled, and on the fact that the city sizes are heavy-tailed distributed.

scholarly journals A Method for Confidence Intervals of High Quantiles

Entropy ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. 70
Author(s):  
Mei Ling Huang ◽  
Xiang Raney-Yan
Keyword(s):  
Confidence Intervals ◽  
Computational Algorithm ◽  
Geometric Mean ◽  
Asymptotic Properties ◽  
Quantile Estimation ◽  
Heavy Tailed Distributions ◽  
High Quantiles ◽  
High Quantile ◽  
Heavy Tailed ◽  
Infinite Moments

The high quantile estimation of heavy tailed distributions has many important applications. There are theoretical difficulties in studying heavy tailed distributions since they often have infinite moments. There are also bias issues with the existing methods of confidence intervals (CIs) of high quantiles. This paper proposes a new estimator for high quantiles based on the geometric mean. The new estimator has good asymptotic properties as well as it provides a computational algorithm for estimating confidence intervals of high quantiles. The new estimator avoids difficulties, improves efficiency and reduces bias. Comparisons of efficiencies and biases of the new estimator relative to existing estimators are studied. The theoretical are confirmed through Monte Carlo simulations. Finally, the applications on two real-world examples are provided.

scholarly journals Foresight in cities: on the possibility of a “strategic urban intelligence”

foresight ◽  
2016 ◽  
Vol 18 (5) ◽  
pp. 469-490 ◽  
Author(s):  
Joe Ravetz ◽  
Ian Douglas Miles
Keyword(s):  
Complex Systems ◽  
Analytical Method ◽  
Design Methodology ◽  
Content Type ◽  
Work In Progress ◽  
Strategic Policy ◽  
The Uk ◽  
The City ◽  
Practical Implications ◽  
Practical Recommendations

Purpose This paper aims to review the challenges of urban foresight via an analytical method: apply this to the city demonstrations on the UK Foresight Future of Cities: and explore the implications for ways forward. Design/methodology/approach The methodology is based on the principles of co-evolutionary complex systems, a newly developed toolkit of “synergistic mapping and design”, and its application in a “synergy foresight” method. Findings The UK Foresight Future of Cities is work in progress, but some early lessons are emerging – the need for transparency in foresight method – and the wider context of strategic policy intelligence. Practical implications The paper has practical recommendations, and a set of propositions, (under active discussion in 2015), which are based on the analysis. Originality/value The paper aims to demonstrate an application of “synergy foresight” with wide benefits for cities and the communities within them.

Game Mechanics as Thinking Mechanisms for Urban Development

2020 ◽  
pp. 215-251
Author(s):  
Teodora Constantinescu ◽  
Oswald Devisch ◽  
Georgi Kostov
Keyword(s):  
Complex Systems ◽  
Urban Development ◽  
Serious Games ◽  
Development Strategies ◽  
Social Awareness ◽  
Knowledge Generation ◽  
Transfer Of Knowledge ◽  
Game Mechanics ◽  
The One ◽  
The City

We witness a growing interest from urban designers in technology to understand cities as complex systems. However, more than often, the use of such technologies is a one-way knowledge generation, meaning that the urban designer is the one benefiting the most. Serious games have the ability to create concepts that lead to a better understanding of the issues that arise in urban development, improving society's implication in the process. This chapter addresses the potential of serious game mechanics to produce mutual transfer of knowledge and solutions able to enhance urban development strategies. Serious games can be one possible answer to motivate citizens and create social awareness and appropriation. Discussing the City Makers game prototype, authors underline the advantages of game mechanics as thinking mechanisms in improving urban development dynamics.

scholarly journals Proportional cancer incidence according to selected sites: comparison between residents in the City of S. Paulo, Brazil: Japanese and Brazilian/Portuguese descent

1991 ◽  
Vol 25 (3) ◽  
pp. 188-192 ◽  
Author(s):  
José Maria Pacheco de Souza ◽  
Sabina Léa Davidson Gotlieb ◽  
Moacyr Lobo da Costa Júnior ◽  
Ruy Laurenti ◽  
Antonio Pedro Mirra ◽  
...  
Keyword(s):  
Public Health ◽  
Confidence Intervals ◽  
Cancer Incidence ◽  
Brazilian Portuguese ◽  
Reference Period ◽  
School Of Public Health ◽  
The University ◽  
The City ◽  
Japanese Descent

The percentual distributions of selected sites of cancer cases according to origin, sex and age are compared. Data were obtained from the Registry of Cancer of S. Paulo (School of Public Health of the University of S. Paulo, Brazil). The reference period for inhabitants of Japanese descent was 1969/78 and for those of Brazilian descent, the period was 1969/75. Standardized Proportionate Incidence Ratios (SPIR) with approximate 95% Confidence Intervals (CI) were evaluated using age specific Incidence Ratios of S. Paulo, 1973, as standards. The results agree with findings of previous works on mortality, but show different patterns according to origin. The well known fact that some sub-groups of a population may be different from the overall group is once again brought to the fore. Attention should be drawn to the differences detected for stomach, skin and prostate, in males, and for stomach, skin, cervix and uterus in females.

scholarly journals Análisis de concordancia de atributos en color de piezas galvanizadas

2019 ◽  
pp. 1-6
Author(s):  
Mario Iván Salas-Dominguez ◽  
Ismael Muñoz-Díaz
Keyword(s):  
Confidence Intervals ◽  
Measurement System ◽  
Kappa Coefficient ◽  
Color Characteristic ◽  
Analysis Tool ◽  
Metal Parts ◽  
Hot Rolled ◽  
The City

The objective of this work is to establish the reliability of the measurement system by attributes in the color characteristic for the galvanized parts as final product. Six operators were evaluated with 30 samples of galvanized metal parts cold and hot rolled in a proportion of 50% of accepted parts and 50% rejected by the quality staff of the Techengineering plant in the city of Aguascalientes, Aguascalientes, under a criterion of passes-does not pass. To carry out the study, the attribute agreement analysis tool of Minitab®16 was used. According to the Fleiss Kappa coefficient and confidence intervals generated in the report, it was established that the accuracy of the system is valued between excellent and good and the accuracy as good marginally, with this information it was possible to establish strategies to improve the measurement system.

scholarly journals The Sociolinguistic Sampling. Does it Need to be Redefined?

2020 ◽  
Vol 3 (4) ◽  
pp. p57
Author(s):  
Francisco García Marcos
Keyword(s):  
New York ◽  
New York City ◽  
Confidence Intervals ◽  
York City ◽  
Representative Sample ◽  
Social Variation ◽  
The Social ◽  
Spanish Populations ◽  
The City ◽  
Representative Samples

The present article analyses a classic in the methodology on the analysis of the social variation of languages: the application of the ratio of 0'0025 % to obtain a representative sample of the population of a speaking community. This ratio, established empirically by Labov in 1966 for New York City, nevertheless presents important limitations when moving to communities with smaller populations. Replicating the empirical experimentation in four Spanish populations of different demographic size, it is shown that the empirically representative samples correspond to the confidence intervals already provided by the general statistics. Likewise, it is shown that these were the parameters between which 0,0025 % in the city of New York was developed. Consequently, the problem was not in the formulation of the ratio by Labov (1966), but in the subsequent indiscriminate application that has been made of it.

scholarly journals Why Do Big Data and Machine Learning Entail the Fractional Dynamics?

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 297
Author(s):  
Haoyu Niu ◽  
YangQuan Chen ◽  
Bruce J. West
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Complex Systems ◽  
Fractional Order ◽  
Big Data Analytics ◽  
Future Research ◽  
Fractional Dynamics ◽  
Complex Signals ◽  
Heavy Tailed Distributions ◽  
Heavy Tailed

Fractional-order calculus is about the differentiation and integration of non-integer orders. Fractional calculus (FC) is based on fractional-order thinking (FOT) and has been shown to help us to understand complex systems better, improve the processing of complex signals, enhance the control of complex systems, increase the performance of optimization, and even extend the enabling of the potential for creativity. In this article, the authors discuss the fractional dynamics, FOT and rich fractional stochastic models. First, the use of fractional dynamics in big data analytics for quantifying big data variability stemming from the generation of complex systems is justified. Second, we show why fractional dynamics is needed in machine learning and optimal randomness when asking: “is there a more optimal way to optimize?”. Third, an optimal randomness case study for a stochastic configuration network (SCN) machine-learning method with heavy-tailed distributions is discussed. Finally, views on big data and (physics-informed) machine learning with fractional dynamics for future research are presented with concluding remarks.

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