TITIP GUSTIA AYU Primary Author mixed material bibliography Bandung Magister Statistika Terapan 2013 id Indonesia

x,; 51hlm,;29,4cm In the method of Partial Least Square (PLS), there are three types of inner approximation weight scheme is used to combine several adjacent latent variables (LV's neighboring) to obtain estimates of the latent variables given the I Centroid 2Factorial Schem~, 3Path weighting Scheme. The three types ~f scheme are made by following certain logic, as an example if the third scheme is used for the same case, will give different results. To determine differences in the three conducted the study using Monte Carlo simulation with a number of scenarios that represent a particular data characteristics that vary the number of samples, patterns of distribution (skewness and kurtosis), and outliers. From the simulation results it can be concluded that, in general scheme factors provide results better suited to data with a relatively small sample size (n = 20). As for the data with relatively large sample size (n = 50, 100, 250 and 500) and the non-normal path scheme is more suitable results, related to the size of Gof and the R-square and bias. Centroid scheme is more suitable for the type of data with a normal distribution for all types of sample size. TITIP GUSTIA AYU Inner Weight Scheme, Partial Least Square (PLS), M 519.5 Ayu p Perpustakaan Universitas Padjadjaran Kementerian Riset Teknologi dan Pendidikan Tinggi 519.5 Ayu p/R.14.16 01001130700004 Perpustakaan Pusat (REF.14.16) 519.5 Ayu p/R.14.16 20%252Fscan0001.jpg.jpg 9775 2017-04-01 15:42:27 2018-05-17 10:19:05 machine generated