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

In the method of Partial Least Square (PLS), there are three types of inner
approximation weight scheme is used to combine several adjacent ...

  • CodeCallNoLokasiKetersediaan
    01001130700004519.5 Ayu p/R.14.16Perpustakaan Pusat (REF.14.16)Tersedia
  • Perpustakaan
    Judul Seri
    -
    No. Panggil
    519.5 Ayu p/R.14.16
    Penerbit Magister Statistika Terapan : Bandung.,
    Deskripsi Fisik
    x,; 51hlm,;29,4cm
    Bahasa
    Indonesia
    ISBN/ISSN
    -
    Klasifikasi
    519.5 Ayu p
    Tipe Isi
    -
    Tipe Media
    -
    Tipe Pembawa
    -
    Edisi
    -
    Subyek
    Inner Weight Scheme, Partial Least Square (PLS), M
    Info Detil Spesifik
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    Pernyataan Tanggungjawab
  • 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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