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Canonical correlation analysis for functional data

References Krzyśko M. (2009): Podstawy wielowymiarowego wnioskowania statysty- cznego [Foundations of multidimensional statistical inference]. Wydawnictwo Naukowe UAM, Poznan. Leurgans S.E., Moyeed R.A., Silverman B.W. (1993): Canonical correlation analy- sis when the data are curves. Journal of the Royal Statistical Society B 55(3): 725{740. Ramsay J.O., Danzell C.J. (1991): Some tools for functional data analysis. Journal of the Royal Statistical Society B 53: 539-572. Ramsay J

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Genetic Variability, Inheritance and Correlation for Mineral Contents in Cabbage (Brassica Oleracea Var. Capitata L.)

, 1950 to 1999. J. Amer. Coll. Nutr. 23 : 669-682. Dewey D.R., Lu K.H. 1959. A correlation and path analysis of components of crested wheat grass seed production. Agronomy J. 51: 515-518. Farnham M.W., Grusak M.A., Wang M. 2000. Calcium and magnesium concentration of inbred and hybrid broccoli heads. J. Amer. Soc. Hortic. Sci. 125 (3): 344-349. Garvin D.F., Welch R.M., Finley J.W. 2006. Historical shifts in the seed mineral micronutrient concentration of US hard red winter wheat germplasm. J. Sci. Food Agric. 86: 2213

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Comparison of some correlation measures for continuous and categorical data

Summary

In the literature there can be found a wide collection of correlation and association coefficients used for different structures of data. Generally, some of the correlation coefficients are conventionally used for continuous data and others for categorical or ordinal observations. The aim of this paper is to verify the performance of various approaches to correlation coefficient estimation for several types of observations. Both simulated and real data were analysed. For continuous variables, Pearson’s r 2 and MIC were determined, whereas for categorized data three approaches were compared: Cramér’s V, Joe’s estimator, and the regression-based estimator. Two method of discretization for continuous data were used. The following conclusions were drawn: the regression-based approach yielded the best results for data with the highest assumed r 2 coefficient, whereas Joe’s estimator was the better approximation of true correlation when the assumed r 2 was small; and the MIC estimator detected the maximal level of dependency for data having a quadratic relation. Moreover, the discretization method applied to data with a non-linear dependency can cause loss of dependency information. The calculations were supported by the R packages arules and minerva.

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Varietal performance and correlation of okra pod yield and yield components

., Olawuyi, O. J., Abdulmaliq, S. Y., Ige, S. A., Mahamood, J., Azeez. M. A. Afolabi, M. S. (2014), Yield performance and adaptation of early and intermediate droughttolerant maize genotypes in Guinea savanna of Nigeria. Sarhad J. Agric. 30(1), 53‒66. [15] Bello, O. B., Olawuyi, O. J. (2015). Gene action, heterosis, correlation and regression estimates in developing hybrid cultivars in maize. Trop. Agric. 92(2), 102‒117. [16] Adekoya, M. A., Ariyo, O. J., Kehinde, O. B., Adegbite, A. E. (2014), Correlation and path analyses of seed yield in

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Coefficient Analysis and Association between Morpho-Agronomical Characters in Common Bean (Phaseolus vulgaris L.)

References Board J.E., Kang M.S., Harville B.G., 1999 - Path analyses of the yield formation process for late-planted soybean. Agron. J., 91:128-135. Bozoglu H., Gulumser A., 1999 - An investigation on the determination correlations and heritabilities of some agronomical characters in Dry Bean (Phaseolus vulgaris L.). Third Field Crops Congress (15-18 November, 1999). Pasture, Forage Crops and Edible Legumes, 3: 360-365. Cokkizgin A., Colkesen M., Idikut L., Ozsisli B., Girgel U., 2013 - Determination of

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Heterosis and heterobeltiosis of yield associated traits in rapeseed cultivars under limited nitrogen application

characters in rapeseed. In Suranaree Journal of Science and Technology , vol. 17 , 2010, pp. 39-47. KATIYAR, R.K. - CHAMOLA, R. - CHOPRA, V.L. 2000. Heterosis and combining ability in Indian mustard ( Brassica juncea ). In Indian Journal of Genetics and Plant Breeding , vol. 60 , 2000, no. 4, pp. 557-559. KHAN, S. - FARHATULLAH, I. - KHALLIL, H. 2008. Phenotypic correlation analysis of elite F3 : 4 Brassica populations for quantitative and qualitative traits. In ARPN Journal of Agricultural and Biological Science , vol. 3 , 2008, pp

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Physio-genetic behavior of maize seedlings at water deficit conditions

. Ashraf M., 1989 - Effect of water stress on maize cultivars during the vegetative stage. Ann. Arid Zone 28: 47-55 Bocev B.V., 1963 - Maize selection at an initial phase of development. Kukuruzu (Maize). Pl. Br. Abat 1:54 Dewey O.R., K.H. Lu, 1959 - A correlation and path coefficient analysis of components of crested wheatgrass seed production. J. Agron 57: 515-518 Ehlig C.F., R.D. Lemert, 1976 - Water use and productivity of wheat under five irrigation treatments. Soil Sci. Soc. Am. J 40: 750-755 Jones

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EVALUATION OF YIELD AND YIELD COMPONENTS CHICKPEA (CICER ARIETINUM L.) IN INTERCROPPING WITH SPRING BARLEY (HORDEUM VULGARE L.)

pants grown with exogenous phosphorus in different cropping system. Aus. J.Exp. Agric. 47: 583-589. Sharma R.K., Bangar K.S., Sharma S.R., Gwal H.B., Verma I.D., 1993 - Studies on intercropping of pulses in spring planted sugarcane. Indian Journal of Pulses Research 6(2), 161-164. Singh D.K., Yadav D.S., 1992 - Production potential and economics of chickpea (Cicer arietinum) -based intercropping systems under rainfed condition. Indian Journal of Agronomy 37(3), 424-429. Singh R., Joshi B.S., Singh S., 1982 - Correlation

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Polish Soil Classification, 6th edition – principles, classification scheme and correlations

Science Annual 69(4): 206–214. Kabała C., Świtoniak M., Charzyński P., 2016. Correlation between the Polish Soil Classification (2011) and international soil classification system World Reference Base for Soil Resources (2015). Soil Science Annual 67(2): 88–100. Kabała C., Waroszewski J., Bogacz A., Łabaz B., 2012. On the specifics of Podzols in mountain areas. Soil Science Annual 63(2): 55–64. Kacprzak A., Drewnik M., Uzarowicz Ł., 2006. Rozwój i kierunki przemian węglanowych gleb rumoszowych na terenie Pienińskiego parku Narodowego. Pieniny

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Approximation of the WRB reference group with the reapplication of archive soil databases

. Geoderma 155, 344-350. [8] Zádorová, T., Penížek, V. (2011), Problems in correlation of Czech national soil classification and World Reference Base 2006. Geoderma 167-168, 54-60. [9] Pásztor, L., Szabó, J., Bakacsi, Zs., Laborczi, A. (2013), Elaboration and applications of spatial soil information systems and digital soil mapping at Research Institute for Soil Science and Agricultural Chemistry of the Hungarian Academy of Sciences. Geocarto International 28(1), 13-27. [10] Huyssteen, C. W., Michéli, E., Fuchs, M., Waltner

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