Big Data as a Source for Official Statistics
暂无分享,去创建一个
Piet Daas | Bart Buelens | Marco Puts | Paul A.M. van den Hurk | P. Daas | M. Puts | B. Buelens | P. V. D. Hurk
[1] Piet Daas,et al. Selectivity of Big data , 2014 .
[2] Rachel Schutt,et al. Doing Data Science , 2013 .
[3] P. Daas,et al. Social media sentiment and consumer confidence , 2014 .
[4] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[5] William H. Sackley. Consumer Confidence Surveys: Do They Boost Forecasters' Confidence? , 2003 .
[6] C. Granger,et al. Co-integration and error correction: representation, estimation and testing , 1987 .
[7] R. Groves. Three Eras of Survey Research , 2011 .
[8] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[9] Joyce Neroni,et al. Twitter as a potential data source for statistics , 2012 .
[10] Din J. Wasem,et al. Mining of Massive Datasets , 2014 .
[11] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001 .
[12] Nello Cristianini,et al. Nowcasting the mood of the nation , 2012, Significance.
[13] J. Manyika. Big data: The next frontier for innovation, competition, and productivity , 2011 .
[14] Edwin de Jonge,et al. Visualizing and Inspecting Large Datasets with Tableplots , 2013, Journal of Data Science.
[15] Brendan T. O'Connor,et al. From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series , 2010, ICWSM.
[16] Rob Kitchin. What does big data mean for official statistics , 2015 .
[17] Cynthia Rudin,et al. Discovery with Data: Leveraging Statistics with Computer Science to Transform Science and Society , 2014 .
[18] Benjamin Fry,et al. Visualizing data - exploring and explaining data with the processing environment , 2008 .
[19] Scott A. Golder,et al. Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures , 2011 .
[20] Eszter Hargittai,et al. Internet Access and Use in Context , 2004, New Media Soc..
[21] C. Lynch. Big data: How do your data grow? , 2008, Nature.
[22] Edward I. George,et al. Bayes and big data: the consensus Monte Carlo algorithm , 2016, Big Data and Information Theory.
[23] Iryna Gurevych,et al. Can We Hide in the Web? Large Scale Simultaneous Age and Gender Author Profiling in Social Media Notebook for PAN at CLEF 2013 , 2013, CLEF.
[24] Leo Breiman,et al. Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author) , 2001, Statistical Science.
[25] Robert J. Elliott,et al. Discrete time filters for doubly stochastic poisson processes and other exponential noise models , 1999 .
[26] Emmanuel Sirimal Silva,et al. Data Mining and Official Statistics: The Past, the Present and the Future , 2014, Big Data.
[27] Piet Daas,et al. Shifting paradigms in official statistics , 2012 .