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The data sets are invariably multivariate and multiway, having dimensions at least product × sensory attribute × people.
The large sensitivity, high reproducibility and essentially unlimited dynamic range of real-time PCR to measure gene expression in complex samples provides the opportunity for powerful multivariate and multiway studies of biological phenomena.
Only small differences in scores were seen and the genes were grouped the same way as in Figure 5 While PCA is a very robust approach to classify samples based on multivariate and multiway measurements and an excellent tool to unravel variable patterns, there are also other techniques for unsupervised clustering.
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Univariate, multivariate PLS and multiway N-PLS models were built to relate these end granule properties to the in-line-measured particle size distribution.
Channel-by-channel and multiway methods are presented.
A novel and flexible approach based on the combination of hidden segmental semi-Markov models (HSMM) and multiway principal component analysis (MPCA) is proposed.
Based on the directions of signal transmission, relaying systems can be classified into three transmission types (i.e., one-way, two-way, and multiway).
We will also subject the results to extensive deterministic (one, two and multiway) sensitivity analysis.
In the next section, we give a brief background on clustering and multiway analysis of post-genomic data, spoligotyping, and MIRU typing.
We will conduct one-way and multiway sensitivity analyses, and a probabilistic sensitivity analyses to estimate the joint uncertainty in cost and effect parameters.
An assessment of the sensitivity of the results obtained to variation in measured resource use, effectiveness and/or unit costs will be undertaken using appropriate one-way and multiway sensitivity analyses.
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