<rdf:RDF xmlns:community="http://www.bibsonomy.org/ontologies/2008/05/community#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:admin="http://webns.net/mvcb/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:cc="http://web.resource.org/cc/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:swrc="http://swrc.ontoware.org/ontology#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xml:base="http://www.bibsonomy.org/tag/statistics"><owl:Ontology rdf:about=""><rdfs:comment>BibSonomy publications for /tag/statistics</rdfs:comment><owl:imports rdf:resource="http://swrc.ontoware.org/ontology/portal"/></owl:Ontology><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2efe71cffdb81b780e72dffa61e03f60b/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2efe71cffdb81b780e72dffa61e03f60b/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.jstor.org/stable/3783842"/><swrc:date>Thu Sep 04 15:27:07 CEST 2008</swrc:date><swrc:journal>Wildlife Society Bulletin</swrc:journal><swrc:number>4</swrc:number><swrc:pages>875--881</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Allen Press"/></swrc:publisher><swrc:title>Landscape Fragmentation Assessment Using a Single Measure</swrc:title><swrc:volume>28</swrc:volume><swrc:year>2000</swrc:year><swrc:keywords>spatial landscape fragmentation geostatistics statistics </swrc:keywords><swrc:abstract>Measurement of fragmentation is crucial for determining its consequences and to develop policy for nature conservation. We propose a fragmentation measure |Ï†| which combines, using a multidimensional Euclidean distance, 4 main characteristics of fragmented landscapes: total habitat area, total habitat perimeter, number of patches, and patch isolation. Its properties can be summarized as: 1) |Ï†| reflects the overall fragmentation status; 2) every component of |Ï†| is accepted as a measure of fragmentation; 3) every component of |Ï†| is a normalized variable; 4) every component of |Ï†| is easy to compute; 5) average patch size, interior habitat, and habitat connectedness are included indirectly in |Ï†|; 6) |Ï†| is independent of the land-use type; and 7) |Ï†| can be calculated for raster and vector data. We show that the normalized values composing |Ï†| prevent misinterpretation of features as fragment number or boundary length. A sensitivity analysis, based upon artificial patterns, showed that increasing fragmentation is correlated with smaller values of |Ï†|. Wildlife managers are encouraged to use |Ï†| for objective evaluation of fragmented landscapes.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="00917648" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="Winter, 2000" swrc:key="formatteddate"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="" swrc:key="language"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="Copyright Â© 2000 Allen Press" swrc:key="copyright"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="" swrc:key="issuetitle"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="primary_article" swrc:key="articletype"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Jan Bogaert"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Piet Van Hecke"/></rdf:_2><rdf:_3><swrc:Person swrc:name="David Salvador-Van Eysenrode"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Ivan Impens"/></rdf:_4></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/213116459478f64c633187a6ad6c9f438/andreab"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/213116459478f64c633187a6ad6c9f438/andreab"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><swrc:date>Thu Sep 04 14:52:17 CEST 2008</swrc:date><swrc:journal>JOURNAL OF GEOPHYSICAL RESEARCH</swrc:journal><swrc:title>Fractal properties of isolines at varying altitude revealing different dominant geological processes on Earth  </swrc:title><swrc:volume>113</swrc:volume><swrc:year>2008</swrc:year><swrc:keywords>physics 2008 geophysics geomorphology statistics myown isoline fracal fractals </swrc:keywords><swrc:abstract>Geometrical properties of landscapes result from the geological processes that have acted through time. The quantitative analysis of natural relief represents an objective form of aiding in the visual interpretation of landscapes, as studies on coastlines, river networks, and global topography, have shown. Still, an open question is whether a clear relationship between the quantitative properties of landscapes and the dominant geomorphologic processes that originate them can be established. In this contribution, we show that the geometry of topographic isolines is an appropriate observable to help disentangle such a relationship. A fractal analysis of terrestrial isolines yields a clear identification of trenches and abyssal plains, differentiates oceanic ridges from continental slopes and platforms, localizes coastlines and river systems, and isolates areas at high elevation (or latitude) subjected to the erosive action of ice. The study of the geometrical properties of the lunar landscape supports the existence of a correspondence between principal geomorphic processes and landforms. Our analysis can be easily applied to other planetary bodies.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Andrea Baldassarri"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Marco Montuori"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Olga Prieto-Ballesteros"/></rdf:_3><rdf:_4><swrc:Person swrc:name="Susanna C. Manrubia"/></rdf:_4></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/26142ad4f2e6c458612017e49d182e469/mschuber"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/26142ad4f2e6c458612017e49d182e469/mschuber"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.jstor.org/pss/1422689"/><swrc:date>Mon Sep 01 14:32:20 CEST 2008</swrc:date><swrc:journal>The American Journal of Psychology</swrc:journal><swrc:number>3/4</swrc:number><swrc:pages>441-471</swrc:pages><swrc:title>The Proof and Measurement of Association between Two Things</swrc:title><swrc:volume>100</swrc:volume><swrc:year>1987</swrc:year><swrc:keywords>statistics ranking correlation </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="C. Spearman"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2b60c2704f273529eb9bd70982f5c38a3/falkowski"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2b60c2704f273529eb9bd70982f5c38a3/falkowski"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Misc"/><owl:sameAs rdf:resource="http://epp.eurostat.ec.europa.eu/"/><swrc:date>Tue Aug 26 19:00:22 CEST 2008</swrc:date><swrc:title>Cultural Statistics, http://epp.eurostat.ec.europa.eu/, (retrieved 23/08/2008)</swrc:title><swrc:year>2007</swrc:year><swrc:keywords>culture statistics </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name=" Eurostat"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2ca976047487b399bdac738eaeea5007a/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2ca976047487b399bdac738eaeea5007a/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.jstor.org/stable/2245115"/><swrc:date>Thu Aug 21 17:54:06 CEST 2008</swrc:date><swrc:journal>The Annals of Applied Probability</swrc:journal><swrc:month>aug</swrc:month><swrc:number>3</swrc:number><swrc:pages>577--602</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Institute of Mathematical Statistics"/></swrc:publisher><swrc:title>Hidden Markov Random Fields</swrc:title><swrc:volume>5</swrc:volume><swrc:year>1995</swrc:year><swrc:keywords>statistics markovrandomfields bayes models imageprocessing </swrc:keywords><swrc:abstract>A noninvertible function of a first-order Markov process or of a nearest-neighbor Markov random field is called a hidden Markov model. Hidden Markov models are generally not Markovian. In fact, they may have complex and long range interactions, which is largely the reason for their utility. Applications include signal and image processing, speech recognition and biological modeling. We show that hidden Markov models are dense among essentially all finite-state discrete-time stationary processes and finite-state lattice-based stationary random fields. This leads to a nearly universal parameterization of stationary processes and stationary random fields, and to a consistent nonparametric estimator. We show the results of attempts to fit simple speech and texture patterns.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="10505164" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="Aug., 1995" swrc:key="formatteddate"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="" swrc:key="language"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="Copyright © 1995 Institute of Mathematical Statistics" swrc:key="copyright"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="" swrc:key="issuetitle"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="primary_article" swrc:key="articletype"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Hans Kunsch"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Stuart Geman"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Athanasios Kehagias"/></rdf:_3></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/272071903cadb88c7f3e06d5331a32e77/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/272071903cadb88c7f3e06d5331a32e77/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.sciencedirect.com/science/article/B6V8V-4P40KFJ-2/2/083af0a5d29e75784181fd0b234d7bed"/><swrc:date>Thu Aug 21 17:50:27 CEST 2008</swrc:date><swrc:journal>Computational Statistics &amp; Data Analysis</swrc:journal><swrc:month>oct</swrc:month><swrc:note>Loads of interesting reference within.</swrc:note><swrc:number>2</swrc:number><swrc:pages>855--868</swrc:pages><swrc:title>Hidden Markov random field models for TCA image analysis</swrc:title><swrc:volume>52</swrc:volume><swrc:year>2007</swrc:year><swrc:keywords>statistics models Gabor HiddenMarkovFields bayes </swrc:keywords><swrc:abstract>Tooth Cementum Annulation (TCA) is an age estimation method carried out on thin cross sections of the root of mammalian teeth. Age is computed by adding the tooth eruption age to the count of annual incremental lines which are called tooth rings and appear in the cementum band. The number of rings is computed from an intensity (gray scale) image of the cementum band, by estimating the average ring width and then dividing the area of the cementum band by this estimate. The ring width is estimated by modelling the image by a hidden Markov random field, where intensities are assumed to be pixelwise conditionally independent and normally distributed, given a Markov random field of hidden binary labels, representing the&#034;true scene&#034;. To incorporate image macro-features (the long-range dependence among intensities and the quasi-periodicity in the placement of tooth rings), the label random field is defined by an energy function that depends on a parametric Gabor filter, convolved with the true scene. The filter parameter represents the unknown of main interest, i.e. the average width of the rings. The model is estimated through an EM algorithm, relying on the mean field approximation of the hidden label distribution and allows to predict the locations of the rings in the image.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Katy Klauenberg"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Francesco Lagona"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2788bd25d81ea706392e4ee2a75254497/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2788bd25d81ea706392e4ee2a75254497/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="http://www.cybergeo.eu/index4750.html."/><swrc:date>Tue Aug 19 17:16:00 CEST 2008</swrc:date><swrc:booktitle>11th European Colloquium on Quantitative and Theoretical Geography. Durham Castle, UK</swrc:booktitle><swrc:publisher><swrc:Organization swrc:name="Cybergeo"/></swrc:publisher><swrc:title>The Metropolis-Hastings algorithm, a handy tool for the practice of environmental model estimation : illustration with biochemical oxygen demand data </swrc:title><swrc:year>2001</swrc:year><swrc:keywords>uncertainty models model inference bayes statistics </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="E. Parent F. Torre"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2ac507ed88165ac62a6e3a41f3b0e50ab/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2ac507ed88165ac62a6e3a41f3b0e50ab/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.sciencedirect.com/science/article/B6VC0-459B9P0-C/2/51c3ceb228cde3ed3304364a0920ff7d"/><swrc:date>Tue Aug 19 15:07:09 CEST 2008</swrc:date><swrc:journal>Journal of Econometrics</swrc:journal><swrc:month>00</swrc:month><swrc:number>1-2</swrc:number><swrc:pages>183--206</swrc:pages><swrc:title>Bayes inference in regression models with ARMA (p, q) errors</swrc:title><swrc:volume>64</swrc:volume><swrc:year>1994</swrc:year><swrc:keywords>models mcmc statistics regression inference Bayes ARMA </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Siddhartha Chib"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Edward Greenberg"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2eca2e182789da65a9bccebd62951745e/jgomezdans"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2eca2e182789da65a9bccebd62951745e/jgomezdans"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.jstor.org/stable/2684568"/><swrc:date>Tue Aug 19 15:04:38 CEST 2008</swrc:date><swrc:journal>The American Statistician</swrc:journal><swrc:month>Nov</swrc:month><swrc:number>4</swrc:number><swrc:pages>327-335</swrc:pages><swrc:title>Understanding the Metropolis-Hastings Algorithm</swrc:title><swrc:volume>49</swrc:volume><swrc:year>1995</swrc:year><swrc:keywords>uncertainty kalmanfilter metropolishastings mcmc statistics bayes </swrc:keywords><swrc:abstract>We provide a detailed, introductory exposition of the Metropolis-Hastings algorithm, a powerful Markov chain method to simulate multivariate distributions. A simple, intuitive derivation of this method is given along with guidance on implementation. Also discussed are two applications of the algorithm, one for implementing acceptance-rejection sampling when a blanketing function is not available and the other for implementing the algorithm with block-at-a-time scans. In the latter situation, many different algorithms, including the Gibbs sampler, are shown to be special cases of the Metropolis-Hastings algorithm. The methods are illustrated with examples.</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Siddhartha Chib"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Edward Greenberg"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2cf5bf163501c72023bd13c972b5878c4/tmalsburg"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2cf5bf163501c72023bd13c972b5878c4/tmalsburg"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://www.jstatsoft.org/v21/i12"/><swrc:date>Tue Aug 12 15:41:04 CEST 2008</swrc:date><swrc:journal>Journal of Statistical Software</swrc:journal><swrc:month>9</swrc:month><swrc:number>12</swrc:number><swrc:pages>1--20</swrc:pages><swrc:title>Reshaping Data with the reshape Package</swrc:title><swrc:volume>21</swrc:volume><swrc:year>2007</swrc:year><swrc:keywords>statistics software </swrc:keywords><swrc:day>15</swrc:day><swrc:abstract>This paper presents the reshape package for R, which provides a common framework
for many types of data reshaping and aggregation. It uses a paradigm of ‘melting’ and
‘casting’, where the data are ‘melted’ into a form which distinguishes measured and iden-
tifying variables, and then ‘cast’ into a new shape, whether it be a data frame, list, or
high dimensional array. The paper includes an introduction to the conceptual framework,
practical advice for melting and casting, and a case study.
</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="2007-09-15" swrc:key="accepted"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="2007-09-15" swrc:key="bibdate"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="1548-7660" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="" swrc:key="acknowledgement"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="2007-02-25" swrc:key="submitted"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="JSSOBK" swrc:key="coden"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Hadley Wickham"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/23f0ab3ce7d19a4f0aad7b176977feb39/brightbyte"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/23f0ab3ce7d19a4f0aad7b176977feb39/brightbyte"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><swrc:date>Wed Aug 06 11:08:26 CEST 2008</swrc:date><swrc:journal>The Balancing Act: Combining Symbolic and Statistical Approaches to Language</swrc:journal><swrc:pages>1--26</swrc:pages><swrc:publisher><swrc:Organization swrc:name="MIT Press"/></swrc:publisher><swrc:title>{Statistical Methods and Linguistics}</swrc:title><swrc:year>1996</swrc:year><swrc:keywords>linguistics statistics classic </swrc:keywords><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="S. Abney"/></rdf:_1><rdf:_2><swrc:Person swrc:name="J. Klavans"/></rdf:_2><rdf:_3><swrc:Person swrc:name="P. Resnik"/></rdf:_3></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/248a7ba329b561e16fbb4ec584e38f36e/rebeccalange"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/248a7ba329b561e16fbb4ec584e38f36e/rebeccalange"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Book"/><swrc:date>Fri Jul 18 14:25:32 CEST 2008</swrc:date><swrc:title>Erfassung und Analyse von Tierpopulationen - 
Eine Einführung in Methoden und Anwendungsmöglichkeiten
im Naturschutz</swrc:title><swrc:year>in prep</swrc:year><swrc:keywords>statistics metapopulation dispersal schätzer recapture </swrc:keywords><swrc:abstract>Inhaltsverzeichnis
Vorwort
1 Einführung
2 Population und Metapopulation
2.1 Konzepte und Abgrenzung
2.2 Populationsparameter
3 Methodenwahl und Versuchsplanung
3.1 Methodenwahl und Anwendungsmöglichkeiten
im Naturschutz
3.2 Versuchsplanung und Datenprotokollierung
4 Relative Häufigkeit
4.1 Generelle Grundlagen
4.2 Häufigkeitsindices
4.2.1 Zählungen von Tierspuren
4.2.2 Zählungen von Tieren
4.2.3 Fang von Tieren
4.3 Häufigkeitsklassen
4.4 Schätzmethoden
4.4.1 Linientaxierung und Punkt-Stop-Methoden
4.4.2 Nachweisfrequenzen
4.4.3 Nachbarschaftsdistanzen
4.5 Korrekturfaktoren
5 Absolute Häufigkeit
5.1 Vermutungen
5.2 Totalerfassung
5.2.1 Totalerfassung im Gesamtgebiet
5.2.2 Totalerfassung auf Probeflächen
5.2.2.1 Homogene Untersuchungsgebiete
5.2.2.2 Stratifizierte Erfassung in heterogenen
Untersuchungsgebieten
5.3 Distanzerfassungen zur Schätzung
von Populationsgröße und -dichte
5.3.1 Linientransektschätzungen
5.3.2 Punkt-Radius-Methode
5.4 Abfangen und Hinzufügen von Individuen
5.4.1 Selektives Abfangen und Hinzufügen
(KELKER’s Methode)
5.4.2 Unselektives Abfangen (Fang-Aufwand-
Methoden)
6 Reproduktion und Mortalität
6.1 Reproduktion
6.2 Lebenserwartung
6.3 Mortalität
6.4 Lebenstafeln
7 Markierung-Wiederfang-Analysen
7.1 Grundannahmen von Markierung-
Wiederfang-Analysen
7.2 Geschlossene Populationen (Populationsgröße)
7.2.1 LINCOLN-PETERSEN-Schätzung
7.2.2 Fangfrequenzmodelle
7.2.3 BAYES’sche Schätzverfahren
7.2.4 Modell CAPTURE
7.3 Populationsdichte
7.4 Offene Populationen
7.4.1 Mindest-Populationsgröße und Mindest-
Überlebensraten
7.4.2 JOLLY-SEBER-Modell
7.4.3 MANLY-PARR-Modell
7.4.4 Robuster Versuchsplan
7.4.5 Von der Tagespopulationsgröße zur
Gesamtpopulationsgröße
7.4.6 Ringfund- und Jagdmarkenanalysen
7.4.7 Vergleich von Mortalitätsraten für unterschiedliche
Zeiträume
7.4.8 Separation von Emigration und Mortalität
8 Aktivitätsraum und Dispersion
9 Artenzahl und relative Häufigkeit
von Arten
Appendix I - Bezugsquellen von Computerprogrammen
Appendix II - Computerprogramme
Literatur
Stichwortverzeichnis</swrc:abstract><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Klaus Henle"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Bernd Gruber"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/21180c2b62d74ec836dce01b7466f88d3/andreab"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/21180c2b62d74ec836dce01b7466f88d3/andreab"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="http://portal.acm.org/citation.cfm?id=1367497.1367542"/><swrc:date>Thu Jul 10 17:12:31 CEST 2008</swrc:date><swrc:address>New York, NY, USA</swrc:address><swrc:booktitle>WWW &#039;08: Proceeding of the 17th international conference on World Wide Web</swrc:booktitle><swrc:pages>327--336</swrc:pages><swrc:publisher><swrc:Organization swrc:name="ACM"/></swrc:publisher><swrc:title>Flickr tag recommendation based on collective knowledge</swrc:title><swrc:year>2008</swrc:year><swrc:keywords>flickr co-occurrence yahoo wordnet www2008 tags recommendation tagging statistics imported </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="Beijing, China" swrc:key="location"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="978-1-60558-085-2" swrc:key="isbn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://doi.acm.org/10.1145/1367497.1367542" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="B\&#034;{o}rkur Sigurbj\&#034;{o}rnsson"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Roelof van Zwol"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/27ffee89349e08beef1b55ab9d68ddd30/andreab"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/27ffee89349e08beef1b55ab9d68ddd30/andreab"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="http://portal.acm.org/citation.cfm?id=1341531.1341558&amp;coll=Portal&amp;dl=GUIDE&amp;CFID=20557217&amp;CFTOKEN=93769937"/><swrc:date>Tue Jul 08 11:55:35 CEST 2008</swrc:date><swrc:address>New York, NY, USA</swrc:address><swrc:booktitle>WSDM &#039;08: Proceedings of the international conference on Web search and web data mining</swrc:booktitle><swrc:pages>195--206</swrc:pages><swrc:publisher><swrc:Organization swrc:name="ACM"/></swrc:publisher><swrc:title>Can social bookmarking improve web search?</swrc:title><swrc:year>2008</swrc:year><swrc:keywords>delicious data statistics folksonomy tagging search </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="Palo Alto, California, USA" swrc:key="location"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="978-1-59593-927-9" swrc:key="isbn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://doi.acm.org/10.1145/1341531.1341558" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Paul Heymann"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Georgia Koutrika"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Hector Garcia-Molina"/></rdf:_3></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/26a1a3f30002607e89466f635a61d8fb3/brazovayeye"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/26a1a3f30002607e89466f635a61d8fb3/brazovayeye"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://iospress.metapress.com/openurl.asp?genre=article&amp;issn=1327-2314&amp;volume=10&amp;issue=5&amp;spage=337"/><swrc:date>Thu Jun 19 17:35:00 CEST 2008</swrc:date><swrc:journal>International Journal of Knowledge-Based and
                 Intelligent Engineering Systems</swrc:journal><swrc:number>5</swrc:number><swrc:pages>337--346</swrc:pages><swrc:title>A novel approach to decoding: Exploiting anticipated
                 attack information using genetic programming</swrc:title><swrc:volume>10</swrc:volume><swrc:year>2006</swrc:year><swrc:keywords>genetic Statistics Transform Programming Watermarking, Decoder, algorithms, and (DCT), Genetic Sufficient (GP), Discrete Cosine programming, </swrc:keywords><swrc:abstract>In a water marking system, the decoder structures are
                 mostly fixed. They do not account for the normal
                 processing or intentional attacks. In the present work,
                 a method of automatically modifying the decoder
                 structure in accordance to the given cover image and
                 conceivable attack is illustrated. The proposed Genetic
                 Programming based watermark decoding scheme is a blind
                 one. It exploits the search space regarding types of
                 dependencies of the decoder on different factors.
                 Especially, information pertaining to watermarked cover
                 coefficients is utilized to reduce host interference,
                 while the conceivable-attack information is utilized to
                 circumvent the anticipated distortion. The actual
                 performance of the genetic decoder is assessed through
                 experiments, which justify the use of intelligent
                 search techniques in signal detection/decoding.
                 Simulation results show that the resultant genetic
                 decoder has superior performance as compared to the
                 conventional decoder against the attacks of Checkmark
                 benchmark.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="1327-2314" swrc:key="issn"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Asifullah Khan"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2e2b6acfc8ede3b37cd7612f3372718e2/brazovayeye"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2e2b6acfc8ede3b37cd7612f3372718e2/brazovayeye"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><swrc:date>Thu Jun 19 17:35:00 CEST 2008</swrc:date><swrc:journal>Computers and Chemical Engineering</swrc:journal><swrc:month>28 February</swrc:month><swrc:number>3</swrc:number><swrc:pages>413--425</swrc:pages><swrc:title>Non-linear principal components analysis using genetic
                 programming</swrc:title><swrc:volume>23</swrc:volume><swrc:year>1999</swrc:year><swrc:keywords>component multivariate methods, distillation principal analysis, genetic nonlinear programming, reduction, algorithms, mathematical statistical data plants, systems, statistics, operations, statistics columns, chemical </swrc:keywords><swrc:abstract>Principal components analysis (PCA) is a standard
                 statistical technique, which is frequently employed in
                 the analysis of large highly correlated data sets. As
                 it stands, PCA is a linear technique which can limit
                 its relevance to the non-linear systems frequently
                 encountered in the chemical process industries. Several
                 attempts to extend linear PCA to cover non-linear data
                 sets have been made, and will be briefly reviewed in
                 this paper. We propose a symbolically oriented
                 technique for non-linear PCA, which is based on the
                 genetic programming (GP) paradigm. Its applicability
                 will be demonstrated using two simple non-linear
                 systems and data collected from an industrial
                 distillation column.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="Matlab, Maple, pop=60" swrc:key="notes"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="doi:10.1016/S0098-1354(98)00284-1" swrc:key="doi"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="13 pages" swrc:key="size"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="H. G. Hiden"/></rdf:_1><rdf:_2><swrc:Person swrc:name="M. J. Willis"/></rdf:_2><rdf:_3><swrc:Person swrc:name="M. T. Tham"/></rdf:_3><rdf:_4><swrc:Person swrc:name="G. A. Montague"/></rdf:_4></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2d9b328c29431cca8b74b24fd1e1be471/brazovayeye"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2d9b328c29431cca8b74b24fd1e1be471/brazovayeye"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#InProceedings"/><owl:sameAs rdf:resource="http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/gecco2002/gecco-2002-15.pdf"/><swrc:date>Thu Jun 19 17:35:00 CEST 2008</swrc:date><swrc:address>New York</swrc:address><swrc:booktitle>GECCO 2002: Proceedings of the Genetic and
                 Evolutionary Computation Conference</swrc:booktitle><swrc:month>9-13 July</swrc:month><swrc:pages>889</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Morgan Kaufmann Publishers"/></swrc:publisher><swrc:title>How Statistics Can Help In Limiting The Number Of
                 Fitness Cases In Genetic Programming</swrc:title><swrc:year>2002</swrc:year><swrc:keywords>statistics fitness Cases, entropy, poster paper, genetic programming, algorithms, </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="San Francisco, CA 94104, USA" swrc:key="address"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="1-55860-878-8" swrc:key="isbn"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Mario Giacobini"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Marco Tomassini"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Leonardo Vanneschi"/></rdf:_3></rdf:Seq></swrc:author><swrc:editor><rdf:Seq><rdf:_1><swrc:Person swrc:name="W. B. Langdon"/></rdf:_1><rdf:_2><swrc:Person swrc:name="E. Cant{\&#039;u}-Paz"/></rdf:_2><rdf:_3><swrc:Person swrc:name="K. Mathias"/></rdf:_3><rdf:_4><swrc:Person swrc:name="R. Roy"/></rdf:_4><rdf:_5><swrc:Person swrc:name="D. Davis"/></rdf:_5><rdf:_6><swrc:Person swrc:name="R. Poli"/></rdf:_6><rdf:_7><swrc:Person swrc:name="K. Balakrishnan"/></rdf:_7><rdf:_8><swrc:Person swrc:name="V. Honavar"/></rdf:_8><rdf:_9><swrc:Person swrc:name="G. Rudolph"/></rdf:_9><rdf:_10><swrc:Person swrc:name="J. Wegener"/></rdf:_10><rdf:_11><swrc:Person swrc:name="L. Bull"/></rdf:_11><rdf:_12><swrc:Person swrc:name="M. A. Potter"/></rdf:_12><rdf:_13><swrc:Person swrc:name="A. C. Schultz"/></rdf:_13><rdf:_14><swrc:Person swrc:name="J. F. Miller"/></rdf:_14><rdf:_15><swrc:Person swrc:name="E. Burke"/></rdf:_15><rdf:_16><swrc:Person swrc:name="N. Jonoska"/></rdf:_16></rdf:Seq></swrc:editor></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/2f917f29b3d8920788041d0564a3e45e4/karinnadrowski"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/2f917f29b3d8920788041d0564a3e45e4/karinnadrowski"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Book"/><swrc:date>Thu Jun 19 16:22:54 CEST 2008</swrc:date><swrc:address>New York; London</swrc:address><swrc:booktitle>Applied spatial data analysis with R</swrc:booktitle><swrc:pages>--</swrc:pages><swrc:publisher><swrc:Organization swrc:name="Springer"/></swrc:publisher><swrc:title>Applied spatial data analysis with R</swrc:title><swrc:year>2008</swrc:year><swrc:keywords>spatial_statistics R statistics Bivand </swrc:keywords><swrc:hasExtraField><swrc:Field swrc:value="9780387781709  0387781706" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="226974722" swrc:key="refid"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="Roger S. Bivand"/></rdf:_1><rdf:_2><swrc:Person swrc:name="Edzer J. Pebesma"/></rdf:_2><rdf:_3><swrc:Person swrc:name="Virgilio. Gómez-Rubio"/></rdf:_3></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/27f2f0f656b9fce77906c0857e15fee68/stefano"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/27f2f0f656b9fce77906c0857e15fee68/stefano"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#Article"/><owl:sameAs rdf:resource="http://portal.acm.org/citation.cfm?id=1005385&amp;dl=#"/><swrc:date>Tue Jun 03 22:07:05 CEST 2008</swrc:date><swrc:address>Cambridge, MA, USA</swrc:address><swrc:journal>Computational Linguistics</swrc:journal><swrc:number>1</swrc:number><swrc:pages>95--101</swrc:pages><swrc:publisher><swrc:Organization swrc:name="MIT Press"/></swrc:publisher><swrc:title>The kappa statistic: a second look</swrc:title><swrc:volume>30</swrc:volume><swrc:year>2004</swrc:year><swrc:keywords>statistics nlp </swrc:keywords><swrc:abstract>In recent years, the kappa coefficient of agreement has become the de facto standard for evaluating intercoder agreement for tagging tasks. In this squib, we highlight issues that affect κ and that the community has largely neglected. First, we discuss the assumptions underlying different computations of the expected agreement component of κ. Second, we discuss how prevalence and bias affect the κ measure.</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="0891-2017" swrc:key="issn"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="http://dx.doi.org/10.1162/089120104773633402" swrc:key="doi"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name="B. Di Eugenio"/></rdf:_1><rdf:_2><swrc:Person swrc:name="M. Glass"/></rdf:_2></rdf:Seq></swrc:author></rdf:Description><rdf:Description rdf:about="http://www.bibsonomy.org/bibtex/23331c99299a6300bc655abc0941c1f57/acf"><owl:sameAs rdf:resource="http://www.bibsonomy.org/uri/bibtex/23331c99299a6300bc655abc0941c1f57/acf"/><rdf:type rdf:resource="http://swrc.ontoware.org/ontology#TechnicalReport"/><owl:sameAs rdf:resource="http://www.cnnic.net.cn/html/Dir/2007/12/27/4954.htm"/><swrc:date>Sun Jun 01 16:51:41 CEST 2008</swrc:date><swrc:institution><swrc:Organization swrc:name="China Internet Network Information Center (CNNIC)"/></swrc:institution><swrc:month>2007/12/27</swrc:month><swrc:number>21</swrc:number><swrc:title>CNNIC Releases 2007 Survey Report on China Weblog Market Number of
	Blog Writers Reaches 47 million Equaling One Fourth of Total Netizens</swrc:title><swrc:type>Website</swrc:type><swrc:year>2007</swrc:year><swrc:keywords>statistics internet_user blog internet netizens blogging China </swrc:keywords><swrc:abstract>On Dec. 26th, 2007, CNNIC published “the Survey Report on Blogs in
	China 2007”. According to the report, by the end of Nov. 2007, the
	number of blog spaces has reached 72.82 million in China, and with
	47 million blog writers, it is reaching one fourth of the total netizens.
	This indicates the rapid growth of the blog market in China. 
	
	
	The survey statistics show that by the end of Nov. 2007, the number
	of blog spaces has reached 72.82 million in China, while that of
	blog writers has totaled 47 million, which means that one out of
	every 30 Chinese, or one out of four netizens writes blogs. Also,
	the active blog writers have taken up 36% of the total blog writers,
	approximately 17 million, and the number of valid blog spaces of
	the active blog users is 28.75 million. 
	
	
	By the end of 2006, the number of blog writers was 17.5 million, and
	within one year the increasement reached nearly 30 million, indicating
	the large-scale growth in number of the blog writer group. However,
	as indicated by the survey, the future growth of the blogs will slow
	down: 65% of the investigated said they only registered one blog,
	and showed little tendency to register another in half a year; only
	11% of the investigated said they would definitely register a blog
	in the future half a year. 
	
	
	The survey also indicates that the blog covers almost all the areas
	of people’s daily life, including the cultural, military, economic,
	tourist, living areas, etc. therefore the blog has also become the
	important channel for people to obtain information. Among the blog
	writers surveyed in this report, the male gender take up 43% while
	the female is 57%, which is contrary to the traditional gender ratio
	of 55:45 (male: female) among netizens, and shows a higher popularity
	of blogs among female users. 
	
	
	In terms of major content the blogs covered, 47% of the blogs are
	written about the inner monologues or record of emotions of the writers.
	Next are the narration of daily life, personal interests and hobbies.
	Most of the blogs are for the writers to record their own life status
	and conduct self demonstration, with the blogs having a more and
	more obvious tendency of self-media attributes. 
	
	
	The survey also finds that among the motives for reading blogs, entertainment
	comes first, which is reported to occupy 43% of the surveyed. It
	will become one of the directions for further probing of the profitable
	blog model to make full use of the participative, interactive, and
	circulative characteristics of the blog and dig out the entertainment
	value of blogs. 
	
	
	In addition, although blogs have become an important information channel,
	the readers obviously have more confident in online news than in
	blog content. 63% of the surveyed said they trust more in the online
	news while only 20% have more trust in the blog content. This shows
	that compared to online news, the blog content at present calls for
	improvement in its credibility. And as a kind of transmission media,
	the blogs need the self discipline of the blog writers in order to
	raise the credibility. 
	
	
	The survey shows, in terms of the methods that blog writers choose
	to access most frequently visited blogs, the primary choice is through
	the links on the blogs and through the browser bookmarks. 12% of
	the blog writers directly key in the blog addresses in the address
	bar, which means 5.64 million blog writers browse their blogs directly
	by keying in the addresses of the blogs. Judging from the accessing
	habits, the market of individual domain names looks optimistic in
	the blog area. 
	
	
	Meanwhile, 66% of the surveyed expressed interests in using the individual
	domain names. And as many as 31% of the surveyed said that if a blog
	website offers the simple or customized blog domain names at 10 yuan/name,
	they would consider changing the blog platforms. So for the 1 yuan
	registration price of .CN domain names, the individual .CN domain
	names would have a lot to commit itself to in the blog area. 
	
	
	The function that blog writers use most frequently is the upload/display
	function of pictures, also with a high frequency in using music and
	videos on the blog. Among the new functions or tools the writers
	mostly long for, the blog writers wish the most is to expand the
	storage of the blogs space, and being provided with the customized
	design models of the blog. Meanwhile，10% of the writers responded
	that they are willing to buy the blog space service. This indicates
	that the functions of blogs have set apart from the monotone written
	record, and headed for multi-functions. 
	
	
	With the continuous progress in Internet technology, the continuous
	expansion of Internet cyberspace, and the continuous raise in networking
	speed, the future blogs will include various technologies such as
	character, images, audio, video, flash, etc., combing the instant
	messaging, social network, online shopping and etc., demonstrating
	having the tendency of becoming the all-around personal space which
	cover all aspects of information of the blog writer. 
	
	
	China Internet Network Information Center (CNNIC), the state network
	information center of China, was founded as a non-profit organization
	on Jun. 3rd 1997. 
	
	CNNIC takes orders from the Ministry of Information Industry (MII)
	to conduct daily business, while it was administratively operated
	by Chinese Academy of Sciences (CAS). Computer Network Information
	Center of Chinese Academy of Sciences takes the responsibility of
	running and administrating CNNIC. CNNIC Steering Committee..</swrc:abstract><swrc:hasExtraField><swrc:Field swrc:value="2008.06.01" swrc:key="timestamp"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="[afeld]" swrc:key="markedentry"/></swrc:hasExtraField><swrc:hasExtraField><swrc:Field swrc:value="afeld" swrc:key="owner"/></swrc:hasExtraField><swrc:author><rdf:Seq><rdf:_1><swrc:Person swrc:name=" CNNIC"/></rdf:_1></rdf:Seq></swrc:author></rdf:Description><foaf:Group rdf:about="http://www.bibsonomy.org/tag/statistics"><foaf:name>statistics</foaf:name><description>Community for tag(s) statistics</description></foaf:Group></rdf:RDF>