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Posted Jul 1, 2019 Updated Nov 30, 2023
By Ernest S.
4 min read

Notes

Short, bite sized thoughts, inspirations, mistakes, and other minutia. The sort of scraps you’d jot down in a notebook to remember for later -peruse the articles tag.

Articles

A collection of long form writing and work processes —mostly about data analysis topics. For shorter, more regular tidbits -peruse the notes tag.

Work & Projects

Curated portfolio of things I’ve done with exploring and analysing datasets in my spare time. Often applied in business settings, or academic research with real world data situations. The output is produce deliverables like insights reports, or predictive models.

Case Study

Usually used in education or practices setting, and helps to demostrate the best practices and successful applications knowledge. The final outcome is presented as a narrative with highlights insights, challenges faced, and lessons lessons learned.

Reference Books

  • ACM (1999) ACM honors Dr. John M. Chambers of Bell Labs with the 1998 ACM software system award for creating “S system” software. ACM press release on 1999-03-23 Brusco M (2004) Clustering binary data in the presence of masking variables. Psychol Methods 9(4):510–523

  • Cliff K (2009) A formative index of segment attractiveness: optimising segment selection for tourism destinations. Ph.D. thesis, School of Management and Marketing, Faculty of Commerce, University of Wollongong

  • Dahl DB (2016) xtable: export tables to LATEX or HTML. https://CRAN.R-project.org/package= xtable, R package version 1.8–2 de Leeuw J, Mair P (2007) An introduction to the special volume on “Psychometrics in R”. J Stat Softw 20(1):1–5

  • Dolnicar S, Grün B (2008) Challenging “factor-cluster segmentation”. J Travel Res 47(1):63–71 Dolnicar S, Grün B (2014) Including ‘don’t know’ answer options in brand image surveys improves data quality. Int J Mark Res 56(1):33–50

  • Dolnicar S, Leisch F (2003) Winter tourist segments in Austria: identifying stable vacation styles for target marketing action. J Travel Res 41(3):281–193

  • Dolnicar S, Leisch F (2008a) An investigation of tourists’ patterns of obligation to protect the environment. J Travel Res 46:381–391

  • Dolnicar S, Leisch F (2008b) Selective marketing for environmentally sustainable tourism. Tour Manag 29(4):672–680

  • Dolnicar S, Leisch F (2010) Evaluation of structure and reproducibility of cluster solutions using the bootstrap. Mark Lett 21:83–101

  • Dolnicar S, Leisch F (2012) One legacy of Mazanec: binary questions are a simple, stable and valid measure of evaluative beliefs. Int J Cult Tour Hosp Res 6(4):316–325, special issue in honour of the contributions of Josef Mazanec to tourism research

  • Dolnicar S, Leisch F (2014) Using graphical statistics to better understand market segmentation solutions. Int J Mark Res 56(2):97–120

  • Dolnicar S, Leisch F (2017) Using segment level stability to select target segments in data-driven market segmentation studies. Mark Lett 28(3):423–436

  • Dolnicar S, Kaiser S, Lazarevski K, Leisch F (2012) Biclustering – overcoming data dimensionality problems in market segmentation. J Travel Res 51(1):41–49

  • Dolnicar S, Grün B, Leisch F (2016) Increasing sample size compensates for data problems in segmentation studies. J Bus Res 69:992–999

  • Ernst D, Dolnicar S (2018) How to avoid random market segmentation solutions. Journal of Travel Research 57(10): 69–82

  • Fox J (2017) Using the R Commander: a point-and-click interface for R. Chapman & Hall/CRC Press, Boca Raton

  • Grün B, Dolnicar S (2016) Response-style corrected market segmentation for ordinal data. Mark Lett 27:729–741

  • Grün B, Leisch F (2007) Fitting finite mixtures of generalized linear regressions in R. Comput Stat Data Anal 51(11):5247–5252

  • Grün B, Leisch F (2008b) Identifiability of finite mixtures of multinomial logit models with varying and fixed effects. J Classif 25(2):225–247

  • Hajibaba H, Dolnicar S (2017) Helping when disaster hits. In: Dolnicar S (ed) Peer-to-peer accommodation networks: pushing the boundaries, chap 21. Goodfellow Publishers, Oxford, pp 235–243 Hajibaba H, Karlsson L, Dolnicar S (2017) Residents open their homes to tourists when disaster strikes. J Travel Res 56(8):1065–1078

  • Hennig C (2000) Identifiability of models for clusterwise linear regression. J Classif 17:273–296 IBM Corporation (2016) IBM SPSS statistics 24. IBM Corporation, Armonk. http://www.ibm. com/software/analytics/spss/

  • Leisch F (2004) FlexMix: a general framework for finite mixture models and latent class regression in R. J Stat Softw 11(8):1–18

  • Leisch F (2006) A toolbox for k-centroids cluster analysis. Comput Stat Data Anal 51(2):526–544 Leisch F (2010) Neighborhood graphs, stripes and shadow plots for cluster visualization. Stat Comput 20(4):457–469

  • Leisch F, Dimitriadou E (2012) mlbench: machine learning benchmark problems. https://CRAN. R-project.org/package=mlbench, R package version 2.1-1

  • Pinheiro J, Bates D, DebRoy S, Sarkar D, R Core Team (2017) nlme: linear and nonlinear mixed effects models. https://CRAN.R-project.org/package=nlme, R package version 3.1-129

  • Sarkar D (2008) Lattice: multivariate data visualization with R. Springer, New York

  • Turner R (2017) deldir: Delaunay triangulation and Dirichlet (Voronoi) tessellation. https://CRAN. R-project.org/package=deldir, R package version 0.1-14

  • Wood SN (2006) Generalized additive models: an introduction with R. Chapman and Hall/CRC, Boca Raton

Contact information.

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