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1	Approximation for Quantile Using Taylor Expansion Chiou, Sheng-Yu 03 July 2012 (has links) Quantile is a basic and an important quantity of a random variable. In some distributions, their quantiles have closed-form expressions. However, for many continuous distributions, the closed-form expressions of their quantiles do not exist. Yu and Zelterman (2011) and Chang (2004) have proposed an approximation of quantiles. In this paper, we propose an improved method which is combined the Taylor expansion with Newton¡¦s method. Some examples are given to compare the computing time of the method we proposed with the methods in Yu and Zelterman (2011) and Chang (2004). Newton's method Median continuous distribution Quantile Taylor expansion
2	Mobility Analysis of Zoo Visitors Byström, Kim January 2019 (has links) In a collaboration between Kolmården Zoo and Linköping University, supported by the Norrköping municipality’s fund for research and innovation, mobility measurements have been performed inside the zoo. These measurements have been done by six WiFi sniﬀers collecting anonymised MAC addresses from the visitors smartphones. The aim of this thesis is to analyse these data to understand visitor ﬂows in the park and other statistics using a model based mobility analysis. The work implies that one can make a rather good prediction of the geographical visitor distribution using this equipment and statistical models. / I ett samarbete mellan Kolmården djurpark och Linköpings universitet, sponsrat av Norrköpingskommuns fond för forskning och utveckling, har rörelsemätningar gjorts inuti parken. Mätningarna har utgjorts av sex WiFi-sniﬀers som samlar in anonymiserade MAC-adresser från besökares smartphones. Målet med detta arbete är att analysera denna data för att förstå besökarﬂöden i parken och annan statistik genom att använda en modellbaserad rörelseanalys. Arbetet visar att man med denna utrsutning och statistiska metoder kan skapa en god prediktion av hur den geograﬁska besökardistributionen ser ut över tid. probe request MAC address Markov model continuous distribution model Monte Carlo simulation Control Engineering Reglerteknik
3	An Automatic Code Generator for Nonuniform Random Variate Generation Leydold, Josef, Derflinger, Gerhard, Tirler, Günter, Hörmann, Wolfgang January 2001 (has links) (PDF) There exists a vast literature on nonuniform random variate generators. Most of these generators are especially designed for a particular distribution. However in pratice only a few of these are available to practioners. Moreover for problems as (e.g.) sampling from the truncated normal distribution or sampling from fairly uncommon distributions there are often no algorithms available. In the last decade so called universal methods have been developed for these cases. The resulting algorithms are fast and have properties that make them attractive even for standard distributions. In this contribution we describe the concept of Automatic random variate generation where these methods are used to produce a single piece of code in a high level programming language. Using a web-based front-end to such a program this is an easy-to-use source for researchers and programmers for high quality generators for a large class of distributions. Using our UNURAN library we have implemented such a system, which is accessable at <a href="http://statistik.wu-wien.ac.at/anuran" target="_blank">http://statistik.wu-wien.ac.at/anuran</a>. / Series: Preprint Series / Department of Applied Statistics and Data Processing MSC 65C10
4	Automatic Nonuniform Random Variate Generation in R Tirler, Günter, Leydold, Josef January 2003 (has links) (PDF) Random variate genration is an important tool in statistical computing. Many programms for simulation or statistical computing (e.g. R) provide a collection of random variate generators for many standard distributions. However, as statistical modeling has become more sophisticated there is demand for larger classes of distributions. Adding generators for newly required distribution seems not to be the solution to this problem. Instead so called automatic (or black-box) methods have been developed in the last decade for sampling from fairly large classes of distributions with a single piece of code. For such algorithms a data about the distributions must be given; typically the density function (or probability mass function), and (maybe) the (approximate) location of the mode. In this contribution we show how such algorithms work and suggest an interface for R as an example of a statistical library. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing MSC 65C10
5	Stetigkeit in der Statistik Huschens, Stefan 30 March 2017 (has links) (PDF) Es werden verschiedene Stetigkeitskonzepte, die in der statistischen Theorie und Methodik eine Rolle spielen, erläutert. Stetige Verteilungsfunktion stetige Zufallsvariable stetigeWahrscheinlichkeitsverteilung absolut stetig stetiges Merkmal -stetiges Ma Stetigkeitskorrektur Continuous distribution function continuous random variable constant probability distribution Absolutely continuous continuous feature continuous measure continuity correction ddc:330 rvk:QH 400
6	Stetigkeit in der Statistik Huschens, Stefan 30 March 2017 (has links) Es werden verschiedene Stetigkeitskonzepte, die in der statistischen Theorie und Methodik eine Rolle spielen, erläutert. info:eu-repo/classification/ddc/330 ddc:330

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