Averaging and exponential smoothing models, www.duke.edu/~rnau/411avg.htm [01.2012].

Barford P., Kline J., Plonka D., Ron A., A signal analysis of network trafic anomalies, w: IMW'02 Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurement, ACM, New York 2002, s. 71-82.

Bertsekas D., Tsitsiklis J., Probabilistic systems analysis and applied probability, http://ocw.mit. edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/lecture-notes [01.2012].

Bollinger J., Bollinger on Bollinger bands, McGraw-Hill, 2001.

Cepstral smoothing, https://ccrma.stanford.edu/~jos/SpecEnv/Cepstral_Smoothing.html [01.2012].

Chandola V., Banerjee A., Kumar V., Anomaly detection. A survey. ACM, "Comput. Surv.", lipiec 2009.

Durbin J., Efficient estimation of parameters in moving-average models, "Biometrika" 1959, nr 3.

Encyklopedia analizy technicznej, www.wdsoftware.com/pl/encyklopedia-at/index.html [01.2012].

Factor analysis, www.psych.cornell.edu/Darlington/factor.htm [23.01.2012].

Fawcett T., An introduction to roc analysis, "Pattern Recogn. Lett." 2006, nr 27, s. 861-874.

Gao J., Hu G., Yao X., Chang R.K.C., Anomaly detection of network traffic based on wavelet packet, APCC '06. Asia-Pacific Conference on Communications, 2006.

Generating mechanical forecasts from statistical models, www.mrp3.com/fcst_models.html [01.2012].

Krzanowski W.J., Principles of multivariate analysis: a user's perspective, "Oxford statistical science series", Oxford University Press, Oxford 2000.

Kumar N., Lolla N., Keogh E., Lonardi S., Ratanamahatana Ch.A., Time-series bitmaps: a practical visualization tool for working with large time series databases, SIAM 2005 Data Mining Conference, SIAM, 2005, s. 531-535.

Lin J., Keogh E., Lonardi S., Chiu B., A symbolic representation of time series, with implications for streaming algorithms, Proceedings of the 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, ACM Press, 2003.

Lo A.W., Mamaysky H., Wang J., Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation, "The Journal of Finance" 2000, nr 55(4), s. 1705-1770.

Murphy J.J., Technical analysis of the financial markets, "Pennsylvania Dental Journal" 1999, nr 77(2).

Naiwny klasyfikator Bayesa, www.statsoft.com.pl/textbook/stnaiveb.html [01.2012].

Ng A., Machine learning, www.ml-class.org/course/auth/welcome [01.2012].

OpenForecastAPI, http://openforecast.sourceforge.net/docs [01.2012].

Smith III J.O., MUS421/EE367B applications lecture b: Cross synthesis using cepstral smoothing or linear prediction for spectral envelopes, https://ccrma.stanford.edu/~jos/SpecEnv/SpecEnv. pdf [01.2012].

Stefanowski J., Analiza szeregów czasowych, www.cs.put.poznan.pl/jstefanowski/aed/TPtimeseries.pdf [01.2012].

Thrun S., Norvig P., Online introduction to artificial intelligence, www.ai-class.com/course/topic/6 [01.2012].

Triple exponential smoothing, www.itl.nist.gov/div898/handbook/pmc/section4/pmc435.htm [01. 2012].

Wei L., Kumar N., Lolla V., Keogh E., Lonardi S., Ratanamahatana Ch.A., Assumption-free anomaly detection in time series, Proceedings of the 17th International Conference on Scientic and Statistical Database Management 2005, s. 237-242.

Wong W.-K., Moore A., Cooper G., Wagner M., Bayesian network anomaly pattern detection for disease outbreaks, Proceedings of the Twentieth International Conference on Machine Learning, Menlo Park, California, lipiec 2003, AAAI Press, s. 808-815.

Wong W.-K., Moore A., Cooper G., Wagner M., What's Strange About Recent Events. "Journal of Urban Health", czerwiec 2003, Supplement 1.

Wong W.-K., Moore A., Cooper G., Wagner M., What's Strange About Recent Events (WSARE): An algorithm for the early detection of disease outbreaks, "Journal of Machine Learning Research" 2005, nr 6.