June 2009

Robustness of the maximum likelihood estimation procedure in factor analysis

  Random variables generated from five distributions were used to represent the common and specific factors in factor analysis in order to determine the robustness of the maximum likelihood estimation procedure. Five response variables were chosen for this study each with two factors. The chosen variables were transformed into linear combinations of an underlying set of hypothesized or unobserved components...

Author(s):   Nwabueze, Joy Chioma, Onyeagu, Sidney I. and Ikpegbu Onyedikachi

June 2009

Statistical analysis of dependence structure of improved cassava varieties in Nigeria

  Multivariate methods were used to analyze a set of data on the proximate compositions of fufuflours processed from 43 different cassava mosaic disease (CMD) resistant varieties from National Root Crop Research Institute (NRCRT) Umudike Nigeria. The factor analysis reveals that three factors accounted for 77.8% of the total variables in the data. Factor 1 has eigenvalue of 3.082, factor 2 has an eigen...

Author(s):   Nwabueze Joy Chioma