Download PDF by Douglas A. Luke: A User's Guide to Network Analysis in R (Use R!)

By Douglas A. Luke

ISBN-10: 3319238833

ISBN-13: 9783319238838

  • presents a pragmatic, hands-on travel of the key community analytic projects R is in a position to, together with community information administration, community visualization, community description, and community modeling
  • comprises all R code wanted for examples used through the book
  • Serves as a good reference source for educating and studying community technological know-how, analytics, and techniques
  • Presenting a finished source for the mastery of community research in R, the aim of community research with R is to introduce glossy community research ideas in R to social, actual, and overall healthiness scientists. The mathematical foundations of community research are emphasised in an available means and readers are guided in the course of the easy steps of community reviews: community conceptualization, information assortment and administration, community description, visualization, and construction and trying out statistical types of networks. as with every of the books within the Use R! sequence, each one bankruptcy comprises huge R code and precise visualizations of datasets. Appendices will describe the R community programs and the datasets utilized in the e-book. An R package deal built particularly for the e-book, to be had to readers on GitHub, comprises correct code and real-world community datasets besides.

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    Extra resources for A User's Guide to Network Analysis in R (Use R!)

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    5620 1. 9110 1. 7911 7 7 6 10 11 11 1. 95 1. 91 1. 44 1. 8144 NV 1969 1973 1977 1981 1985 1987 Number of Carriers 1 / Source: CAB/FAA Data. S. 45 1. 0421 1. 2201 1. 40 1. 2943 1. 8588 1. S. 21 1. 5413 1. 8904 1. 0000 1. 0000 1. 7758 1. 4951 1. 3511 1. 5186 1. 1979 1. S. enplanements 1/ 47 takeovers/acquisitions or less typically, financial failure. 5. These figures show the traffic handled by air carriers serving the airport~ the air carriers are ranked for each airport depending on the proportion of traffic that they handle.

    They claim that the predictions made by Douglas and Miller (1974), (namely, that airline deregulation would benefit travellers because fares would fall, even though quality would decline) are largely inaccurate. The falling fares and service quality, they claim are encountered primarily in pleasure travel between large hubs. The benefits from deregulation accrue mainly to business travelers because of improved service and convenience attributable to the accelerated development, of hub-and-spoke operations and to frequency improvements in low density markets.

    Those measures used in the economics airline studies mentioned above will be contrasted with the Gini index, the coefficient of variation and Theil's entropy measure. Briefly introducing these statistics, the Herfindahl index [Herfindahl (1950)] is computed as H = L (x/~ I X I )2 where x I is the air traffic at airport i (or in the case of an airport's traffic distribution, XI is the air traffic handled by carrier i) 5 . The term ' air traffic' refers to passenger enplanements, unless otherwise indicated.

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    A User's Guide to Network Analysis in R (Use R!) by Douglas A. Luke


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