[Agarwal, S., Jacobs Jr., D. R., Vaidya, D. Sibley, Ch. T., Jorgensen, N. W., Rotter, J. I., Chen, Y.-D. I., et al. (2012). Metabolic Syndrome Derived from Principal Component Analysis and Incident Cardiovascular Events: The Multi Ethnic Study of Atherosclerosis (MESA) and Health, Aging, and Body Composition (Health ABC). Cardiology Research and Practice, 2012. DOI:10.1155/2012/919425.10.1155/2012/919425]Search in Google Scholar
[Aguilera, A. M., Escabias, M., & Valderrama, M. J. (2006). Using principal compo- nents for estimating logistic regression with high-dimensional multicollinear data. Computational Statistics & Data Analysis, 50(8), 1905-1924.10.1016/j.csda.2005.03.011]Search in Google Scholar
[Akinsola, O. M., Nwagu, B. I., Orunmuyi, M., Iyeghe-Erakpotobor, G. T., Eze, E. D., Abanikannda, O. T. F., Onaadepo, O., Okuda, E. U., & Louis, U. (2014). Prediction of bodyweight from body measurements in rabbits using principal component analysis. Annals of Biological Sciences, 2(1), 1-6.]Search in Google Scholar
[Belasco, E., Philips, B. U., & Gong, G. (2012). The Health Care Access Index as a Determinant of Delayed Cancer Detection Through Principal Component Analysis. In P. Sanguansat (Ed.), Principal Component Analysis - Multidis- ciplinary Applications (pp. 143-166). InTech. DOI:10.5772/38460.10.5772/38460]Search in Google Scholar
[Biffi, A., Anderson, Ch. D., Nalls, M. A., Rahman, R., Sonni, A., Cortellini, L., Rost, N. S., et al. (2010). Principal-Component Analysis for Assessment of Population Stratification in Mitochondrial Medical Genetics. The American Journal of Human Genetics, 86(6), 904-917.10.1016/j.ajhg.2010.05.005]Search in Google Scholar
[Brzyski, P., Tobiasz-Adamczyk, B., & Knurowski T. (2012). Trafność i rzetelność skali GARS w populacji osob w starszym wieku w Polsce, Gerontologia Pol- ska, 20(3), 109-117.]Search in Google Scholar
[Czernyszewicz, E. (2008). Zastosowanie analizy głownych składowych do opisu kon- sumenckiej struktury jakości jabłek. Żywność. Nauka. Technologia. Jakość, 2(57), 119-127.]Search in Google Scholar
[Daszykowski,M., &Walczak, B. (2008). Analiza czynnikow głownych i inne metody eksploracji danych. In D. Zuba & A. Parczewski (Eds.), Chemometria w ana- lityce. Krakow: IES.]Search in Google Scholar
[Daszykowski, M., Walczak, B., & Massart, D. L. (2001). Looking for natural pat- terns in data: Part 1. Density-based approach. Chemometrics and Intelligent Laboratory Systems, 56, 83-92.10.1016/S0169-7439(01)00111-3]Search in Google Scholar
[Duch, W., Korbicz, J., Rutkowski, L., & Tadeusiewicz, R. (2000). Biocybernetyka i Inżynieria Biomedyczna 2000. Tom 6: Sieci neuronowe. Warszawa: Aka- demicka Oficyna Wydawnicza Exit.]Search in Google Scholar
[Fisher, R., & MacKenzie, W. (1923). Studies in crop variation II. The manurial response of different potato varieties. Journal of Agricultural Science, 13, 311-320.10.1017/S0021859600003592]Search in Google Scholar
[Furman-Haran, E., Shapiro Feinberg, M., Badikhi, D., Eyal, E., Zehavi, T., & De- gani, H. (2014). Standardization of Radiological Evaluation of Dynamic Con- trast Enhanced MRI: Application in Breast Cancer Diagnosis. Technology in Cancer Research & Treatment, 13(5), 445-454.]Search in Google Scholar
[Gastinel, L. N. (2012). Principal Component Analysis in the Era of “Omisc” Data. In P. Sanguansat (Ed.), Principal Component Analysis - Multidisciplinary Applications (pp. 21-42). InTech. DOI:10.5772/37099.10.5772/37099]Search in Google Scholar
[Giuliani, A., & Benigni, R. (2000). Principal Component Analysis for Descriptive Epidemiology. In R. W. Brause & E. Hanisch (Eds.). Medical Data Analysis. Lecture Notes in Computer Science, 1933, 308-313.10.1007/3-540-39949-6_37]Search in Google Scholar
[Hladnik, A. (2013). Image compression and face recognition: two image process- ing applications of principal component analysis. International Circular of Graphic Education and Research, 6, 56-61.]Search in Google Scholar
[Hoffmann, K., Schulze, M. B., Schienkiewitz, A., Nothlings, U., & Boeing, H. (2004). Application of a New Statistical Method to Derive Dietary Patterns in Nutritional Epidemiology. American Journal of Epidemiology, 159(10), 935-944.10.1093/aje/kwh134]Search in Google Scholar
[Hotelling, H. (1933). Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology, 24, 417-441.10.1037/h0071325]Search in Google Scholar
[Kaur, G., Arora, A. S., & Jain, V. K. (2012). Multiple Linear Regression Model based on Principal Component Scores to Study the Relationship between Anthropometric Variables and BP Reactivity to Unsupported Back in Nor- motensive Post-graduate Females. International conference: 1st, Energy and environment technologies and equipment. Advances in Environment, Biotechnology and Biomedicine (pp. 373-377). Greece: WSEAS.]Search in Google Scholar
[Kolasa-Więcek, A. (2012). Application of PCA in the analysis of parameters related to agricultural greenhouse gases emissions in Europe. Journal of Research and Applications in Agricultural Engineering, 57(1), 77-79.]Search in Google Scholar
[Konieczna, L., & Lamparczyk, H. (2008). Wpływ płci na farmakokinetykę wybra- nych lekow. Zastosowania metod statystycznych w badaniach naukowych III (pp. 299-310).Krakow, Polska: StatSoft Polska. Retreived from: http://www.statsoft.pl/portals/0/Downloads/Wplywplci.pdf. ]Search in Google Scholar
[Koter, S., & Wesołowska, K. (2003). Zastosowanie metody PCA do opisu wod na- turalnych. II Ogólnopolska Konferencja Naukowo-Techniczna “Aktualne za- gadnienia w uzdatnianiu i dystrybucji wody” (pp. 413-420). Szczyrk, Poland.]Search in Google Scholar
[Latifoglu, F., Polat, K., Kara, S., & Gunes, S. (2008). Medical diagnosis of atherosclerosis from Carotid Artery Doppler Signals sing principal compo- nent analysis (PCA), k-NN based weighting pre-processing and Artificial Immune Recognition System (AIRS). Journal of Biomedical Informatics, 41(1), 15-23.10.1016/j.jbi.2007.04.001]Search in Google Scholar
[Ma, S. (2007). Principal Component Analysis in Linear Regression Survival Model with Microarray Data. Journal of Data Science, 5, 183-198.10.6339/JDS.2007.05(2).326]Search in Google Scholar
[Martens, H., & Nas, T. (1991). Multivariate calibration. Chichester: Jon Wiley & Sons.]Search in Google Scholar
[Martis, R. J., Acharya U. R., & Min, L. Ch. (2013). ECG beat classification us- ing PCA, LDA, ICA and Discrete Wavelet Transform. Biomedical Signal Processing and Control, 8(5), 437-448.10.1016/j.bspc.2013.01.005]Search in Google Scholar
[Milewska, A. J., Gorska, U., Jankowska, D., Milewski, R., & Wołczyński, S. (2011). The use of the basket analysis in a research of the process of hospitalization in the gynecological ward. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 25(38), 83-98.]Search in Google Scholar
[Milewska, A. J., Jankowska, D., Cwalina, U., Więsak, T., Morgan, A., & Milew- ski, R. (2013). Analyzing outcome of intrauterine insemination treatment by application of Cluster Analysis or Kohonen Neural Networks. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 35(48), 7-25.10.2478/slgr-2013-0041]Search in Google Scholar
[Milewska, A. J., Jankowska, D., Gorska, U., Milewski, R., & Wołczyński, S. (2012). Graphical representation of the relationships between qualitative variables concerning the process of hospitalization in the gynecological ward using correspondence analysis. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 29(42), 7-25.]Search in Google Scholar
[Milewski, R., Jamiołkowski, J., Milewska, A. J., Domitrz, J., Szamatowicz, J., & Wołczyński, S. (2009). Prognosis of the IVF ICSI/ET procedure efficiency with the use of artificial neural networks among patients of the Depart- ment of Reproduction and Gynecological Endocrinology. Ginekologia Polska, 80(12), 900-906.]Search in Google Scholar
[Milewski, R., Malinowski, P., Milewska, A. J., Czerniecki, J., Ziniewicz, P., & Wołczyński, S. (2011). Nearest neighbor concept in the study of IVF ICSI/ET treatment effectiveness. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 25(38), 49-57.]Search in Google Scholar
[Milewski, R., Milewska, A. J., Czerniecki, J., Leśniewska, M., & Wołczyński, S. (2013a). Analysis of the demographic profile of patients treated for infertility using assisted reproductive +techniques in 2005-2010. Ginekologia Polska, 84(7), 609-614. 21 Milewski, R., Milewska, A. J., Domitrz, J., & Wołczyński, S. (2008). In vitro fer- tilization ICSI/ET in women over 40. Przegląd Menopauzalny, 7(2), 85-90.]Search in Google Scholar
[Milewski, R., Milewska, A. J., Więsak, T., Morgan, A., (2013b). Comparison of artificial neural networks and logistic regression analysis in pregnancy pre- diction using in the in vitro fertilization treatment Networks. Studies in Logic, Grammar and Rhetoric. Logical, Statistical and Computer Methods in Medicine, 35(48), 39-48.10.2478/slgr-2013-0033]Search in Google Scholar
[Mudrova, A., & Prochazka, A. (2005). Principal Component Analysis in Image Processing. Technical Computing Conference, Prague, Czech Republic.]Search in Google Scholar
[Næs, T., Isaksson, T., Fearn, T., & Davies, T. (2002). A user-friendly guide to multivariate calibration and classification. Chichester UK: NIR Publications.]Search in Google Scholar
[Nascimento, E. C. M., & Martins, J. B. L. (2012). Pharmacophoric Profile: De- sign of New Potential Drugs with PCA Analysis. In P. Sanguansat (Ed.), Principal Component Analysis - Multidisciplinary Applications (pp. 59-74). InTech. DOI:10.5772/37426.10.5772/37426]Search in Google Scholar
[Nowicki, J., Żylińska, A., & Kin, A. (2013). Zastosowanie metod statystycznych i graficznych w analizie zdeformowanych tektonicznie trylobitow z rodziny Ellipsocephalidae Matthew, 1887 z kambru Gor Świętokrzyskich. In M. Kę- dzierski & B. Kołodziej (Eds.), XXII Konferencja Naukowa Sekcji Paleonto- logicznej Polskiego Towarzystwa Geologicznego “Aktualizm i antyaktualizm w paleontologii” (pp. 38-39). Tyniec, Poland: Polskie Towarzystwo Geolog- iczne.]Search in Google Scholar
[Pandey, P. K., Singh, Y., & Tripathi, S. (2011). Image Processing using Princi- ple Component Analysis. International Journal of Computer Applications, 15(4), 37-40.10.5120/1935-2582]Search in Google Scholar
[Panek, D. (2014). Ocena parametrow analizy akustycznej w detekcji patologii mowy. Przegląd Elektrotechniczny, R. 90(5), 126-129. DOI: 10.12915/pe. 2014.05.29.]Search in Google Scholar
[Patterson, N., Price, A. L., & Reich, D. (2006). Population Structure and Eigen- analysis. PLoS Genetics, 2(12), 2074-2093. DOI:10.1371/journal.pgen.0020 190.]Search in Google Scholar
[Pearson, K. (1901). On lines and planes of closest fit to systems of points in space. Philosophical Magazine, 2, 559-572.10.1080/14786440109462720]Search in Google Scholar
[Petrisor, A. I., Ianos, I., Iurea, D., & Vaidianu, M. N. (2012). Applications of Principal Component Analysis integrated with GIS. Procedia Environmental Sciences, 14, 247-256.10.1016/j.proenv.2012.03.024]Search in Google Scholar
[Pushpa Rathi, G. V. P., & Palani, S. (2012). Brain Tumor MRI Image Classification with Feature Selection and Extraction using Linear Discriminant Analysis. International Journal of Information Sciences & Techniques, 2(4), 131-146.10.5121/ijist.2012.2413]Search in Google Scholar
[Raskin, R., & Terry, H. (1988). A Principal-Components Analysis of the Narcis- sistic Personality Inventory and Further Evidence of Its Construct Validity. Journal of Personality and Social Psychology, 54(5), 890-902.10.1037/0022-3514.54.5.890]Search in Google Scholar
[Raychaudhuri, S., Stuart, J. M., & Altman, R. (2000). Principal Component Analy- sis to Summarize Microarray Experiments: Application to Sporulation Time Series. Pacyfic Symposium on Biocomputing, 2000, 455-466.]Search in Google Scholar
[Reverter, F., Vegas, E., & Oller, J. M. (2012). Kernel Methods for Dimensionality Reduction Applied to the “Omics” Data. In P. Sanguansat (Ed.), Principal Component Analysis - Multidisciplinary Applications (pp. 1-20). InTech. DOI:10.5772/37431.10.5772/37431]Search in Google Scholar
[Rymuza, K., & Radzka, E. (2013). Zastosowanie analiz wielowymiarowych do oceny jakości wody pitnej. Nauka. Technologia. Jakość, 6(91), 165-174.]Search in Google Scholar
[Santo, R. do E. (2012). Principal Component Analysis applied to digital image compression. Einstein (Sao Paulo), 10(2), 135-139.10.1590/S1679-45082012000200004]Search in Google Scholar
[Scholz, M., Schmidt, S., Loesgen, S., & Bickeb¨oller, H. (1999). Analysis of principal component based quantitative phenotypes for alcoholism. Genetic Epidemi- ology, 17(l), 313-318.10.1002/gepi.1370170753]Search in Google Scholar
[Stuhler, E., &Merhof, D. (2012). Principal Component Analysis Applied to SPECT and PET Data of Dementia Patients - A Review. In P. Sanguansat (Ed.), Principal Component Analysis - Multidisciplinary Applications (pp. 167-186). InTech. DOI:10.5772/38010.10.5772/38010]Search in Google Scholar
[Suchacz, B., & Wesołowski, M. (2010). Relacje pomiędzy zawartością cynku, miedzi, ołowiu i niklu w wodnych ekstraktach z mieszanek ziołowych. Bro- matologia i Chemia Toksykologiczna, 43(4), 485-492.]Search in Google Scholar
[Szefer, P. (2003). Zastosowanie technik chemometrycznych w analitycznej ocenie probek biologicznych i środowiskowych. In J. Namieśnik, W. Chrzanowski & P. Szpinek (Eds.), Nowe Horyzonty i Wyzwania w Analityce i Monitoringu Środowiskowym (pp. 599-629). Gdańsk, Poland: CEEAM.]Search in Google Scholar
[Tabachnick, B. G., & Fidell, L. S. (1996). Using Multivariate Statistics. Boston: Pearson.]Search in Google Scholar
[Ukalska, J., Ukalski, K., Śmiałowski, T., & Mądry, W. (2008). Badanie zmien- ności i wspołzależności cech użytkowych w kolekcji roboczej pszenicy ozi- mej (Triticum aestivum L.) za pomocą metod wielowymiarowych. Część II. Analiza składowych głownych na podstawie macierzy korelacji fenotypowych i genotypowych. Biuletyn Instytutu Hodowli i Aklimatyzacji Roślin, 249, 45-57.]Search in Google Scholar
[Webb, A. R. (2003). Statistical Pattern Recognition. Wiley.]Search in Google Scholar
[Varraso, R., Garcia-Aymerich, J., Monier, F., Le Moual, N., De Batlle, J., Mi- randa, G., Pison, Ch., Romieu, I., Kauffmann, F., & Maccario, J. (2012). Assessment of dietary patterns in nutritional epidemiology: principal com- ponent analysis compared with confirmatory factor analysis. The American Journal of Clinical Nutrition, 96(5), 1079-1092.10.3945/ajcn.112.038109]Search in Google Scholar
[Zuendorf, G., Kerrouche, N., Herholz, K., & Baron, J. C. (2003). Efficient principal component analysis for multivariate 3D voxel-based mapping of brain func- tional imaging data sets as applied to FDG-PET and normal aging. Human Brain Mapping 18(1), 13-21.10.1002/hbm.10069]Search in Google Scholar