PERBANDINGAN INNER WEIGHT SCHEME DALAM METODE PARTIAL LEAST SQUARE (PLS) MELALUI SIMULASI MONTE CARLO

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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.

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Series Title

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Call Number

519.5 Ayu p/R.14.16

Publisher

Bandung : Magister Statistika Terapan., 2013

Collation

x,; 51hlm,;29,4cm

Language

Indonesia

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Classification

519.5 Ayu p

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