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The latest content from StatisticsViews.http://www.statisticsviews.comWeighted linear programming discriminant analysis for high‐dimensional binary classification
http://www.statisticsviews.com/details/journalArticle/11251228/Weighted-linear-programming-discriminant-analysis-forhighdimensional-binary-clas.html
Abstract Linear discriminant analysis (LDA) is widely used for various binary classification problems. In contrast to the LDA that estimates the precision matrix Ω and the mean difference vector δ in the classification rule separately, the linear programming discriminant (LPD) rule estimates the product Ωδ directly through a constrained ℓ1 minimization. The LPD rule has very good classification performance on many high‐dimensional binary classification problems. However, to estimate β* = Ωδ,...]]>2020-07-04T13:39:06ZModelling the travel time of transit vehicles in real‐time through a GTFS‐based road network using GPS vehicle locations
http://www.statisticsviews.com/details/journalArticle/11251232/Modelling-the-travel-time-of-transit-vehicles-in-realtime-through-a-GTFSbased-ro.html
We present a framework for modelling transit vehicles and estimating traffic conditions in real‐time based solely on GTFS data, with an emphasis on the real‐time feasibility of the application.]]>2020-07-04T09:30:01ZRobust estimation for longitudinal data under outcome‐dependent visit processes
http://www.statisticsviews.com/details/journalArticle/11251233/Robust-estimation-for-longitudinal-data-under-outcomedependent-visit-processes.html
Summary In longitudinal data where the timing and frequency of the measurement of outcomes may be associated with the value of the outcome, significant bias can occur. Previous results depended on correct specification of the outcome process and a somewhat unrealistic visit process model. In practice, this will never exactly be the case, so it is important to understand to what degree the results hold when those assumptions are violated in order to guide practical use of the methods. This...]]>2020-07-04T09:24:03ZOn autoregressive model selection for the exponentially weighted moving average control chart of residuals in monitoring the mean of autocorrelated processes
http://www.statisticsviews.com/details/journalArticle/11251231/On-autoregressive-model-selection-for-the-exponentially-weighted-moving-average-.html
Abstract With the development of automation technologies, data can be collected in a high frequency, easily causing autocorrelation phenomena. Control charts of residuals have been used as a good way to monitor autocorrelated processes. The residuals have been often computed based on autoregressive (AR) models whose building needs much experience. Data have been assumed to be first‐order autocorrelated, and first‐order autoregressive (AR(1)) models have been employed to obtain residuals. But...]]>2020-07-04T08:35:47ZWeighted distances in scale‐free preferential attachment models
http://www.statisticsviews.com/details/journalArticle/11251050/Weighted-distances-in-scalefree-preferential-attachment-models.html
We study three preferential attachment models where the parameters are such that the asymptotic degree distribution has infinite variance. Every edge is equipped with a nonnegative i.i.d. weight. We study the weighted distance between two vertices chosen uniformly at random, the typical weighted distance, and the number of edges on this path, the typical hopcount. We prove that there are precisely two universality classes of weight distributions, called the explosive and conservative class. In...]]>2020-07-04T05:52:38ZRetail and Place Attractiveness: The Effects of Big‐Box Entry on Property Values
http://www.statisticsviews.com/details/journalArticle/11251053/Retail-and-Place-Attractiveness-The-Effects-of-BigBox-Entry-on-Property-Values.html
The opponents of big‐box entry argue that large retail establishments generate a variety of negative externalities. The advocates, on the contrary, argue that access to a large retail market not only delivers direct economic benefits, but also a variety of positive spill‐over effects, and therefore, can be considered a consumer amenity that increases the attractiveness of the entry location. To test the validity of these competing arguments, we use the entry of IKEA in Sweden as a...]]>2020-07-04T03:39:44ZOn competitive analysis for polling systems
http://www.statisticsviews.com/details/journalArticle/11251049/On-competitive-analysis-for-polling-systems.html
Abstract Polling systems have been widely studied, however most of these studies focus on polling systems with renewal processes for arrivals and random variables for service times. There is a need driven by practical applications to study polling systems with arbitrary arrivals (not restricted to time‐varying or in batches) and revealed service time upon a job's arrival. To address that need, our work considers a polling system with generic setting and for the first time provides the...]]>2020-07-03T12:10:59ZMore on trees and Cohen reals
http://www.statisticsviews.com/details/journalArticle/11250616/More-on-trees-and-Cohen-reals.html
Abstract In this paper we analyse some questions concerning trees on κ, both for the countable and the uncountable case, and the connections with Cohen reals. In particular, we provide a proof for one of the implications left open in [6, Question 5.2] about the diagram for regularity properties.]]>2020-07-03T05:26:06ZManaging Innovation Spillover in Outsourcing
http://www.statisticsviews.com/details/journalArticle/11250636/Managing-Innovation-Spillover-in-Outsourcing.html
When an innovator outsources the manufacturing of an innovative product to a contract manufacturer (CM) which is also a competitor in the end market, the potential innovation spillover may be a serious concern. We study an innovator’s outsourcing decision under spillover risks with an emphasis on the ex ante uncertain values of innovations, and distinguish between technical innovations which can only spill over through outsourcing and non‐technical innovations which can also spill over in the...]]>2020-07-02T23:10:22ZHomogeneity testing under finite location‐scale mixtures
http://www.statisticsviews.com/details/journalArticle/11250612/Homogeneity-testing-under-finite-locationscale-mixtures.html
Résumé Le problème qui consiste à tester l'ordre d'un modèle de mélange fini possède une longue histoire et demeure un sujet de recherche effervescent. Depuis que les résultats de Ghosh & Sen (1985) ont révélé des propriétés asymptotiques difficiles à gérer du test du rapport de vraisemblance, plusieurs approches de rechange ont été développées avec succès. Le test du rapport de vraisemblance modifié et le test EM mènent notamment à une élégante solution pour un mélange fini de distributions...]]>2020-07-02T18:15:11Z