A B D E G I L N O P R S T U V W X Y
PRiNS-package | Pattern Recognition in the Natural Sciences |
ASCA.2f | Analysis of variance - Simultaneous Component Analysis |
ASCA.3f | Analysis of variance - Simultaneous Component Analysis |
ASCAfun.res | Analysis of variance - Simultaneous Component Analysis |
ASCAfun.triple | Analysis of variance - Simultaneous Component Analysis |
ASCAfun1 | Analysis of variance - Simultaneous Component Analysis |
ASCAfun12 | Analysis of variance - Simultaneous Component Analysis |
ASCAfun2 | Analysis of variance - Simultaneous Component Analysis |
biplot.PCA | Principal Component Analysis plotting functions |
Day | Plant data |
Days | Plant data |
discs | Artificial data sets in three dimensions |
doex | PRiNS exercises and demos |
efa | Evolving Factor Analysis |
exer.2.1.1 | PRiNS exercises and demos |
exer.2.1.10 | PRiNS exercises and demos |
exer.2.1.11 | PRiNS exercises and demos |
exer.2.1.12 | PRiNS exercises and demos |
exer.2.1.2 | PRiNS exercises and demos |
exer.2.1.3 | PRiNS exercises and demos |
exer.2.1.4 | PRiNS exercises and demos |
exer.2.1.5 | PRiNS exercises and demos |
exer.2.1.6 | PRiNS exercises and demos |
exer.2.1.7 | PRiNS exercises and demos |
exer.2.1.8 | PRiNS exercises and demos |
exer.2.1.9 | PRiNS exercises and demos |
exer.2.2.1 | PRiNS exercises and demos |
exer.2.2.2 | PRiNS exercises and demos |
exer.2.2.3 | PRiNS exercises and demos |
exer.2.3.1 | PRiNS exercises and demos |
exer.2.3.2 | PRiNS exercises and demos |
exer.2.3.3 | PRiNS exercises and demos |
exer.2.3.4 | PRiNS exercises and demos |
exer.2.3.5 | PRiNS exercises and demos |
exer.2.3.6 | PRiNS exercises and demos |
exer.2.4.1 | PRiNS exercises and demos |
exer.2.4.2 | PRiNS exercises and demos |
exer.2.4.3 | PRiNS exercises and demos |
exer.2.4.4 | PRiNS exercises and demos |
exer.2.4.5 | PRiNS exercises and demos |
exer.2.4.6 | PRiNS exercises and demos |
exer.2.4.7 | PRiNS exercises and demos |
exer.2.5.1 | PRiNS exercises and demos |
exer.2.5.2 | PRiNS exercises and demos |
exer.2.5.3 | PRiNS exercises and demos |
exer.2.5.4 | PRiNS exercises and demos |
exer.2.5.5 | PRiNS exercises and demos |
exer.2.5.6 | PRiNS exercises and demos |
exer.2.5.7 | PRiNS exercises and demos |
exer.2.5.8 | PRiNS exercises and demos |
exer.2.6.1 | PRiNS exercises and demos |
exer.2.6.2 | PRiNS exercises and demos |
exer.2.6.3 | PRiNS exercises and demos |
exer.3.1.1 | PRiNS exercises and demos |
exer.3.1.2 | PRiNS exercises and demos |
exer.3.1.3 | PRiNS exercises and demos |
exer.3.1.4 | PRiNS exercises and demos |
exer.3.1.5 | PRiNS exercises and demos |
exer.3.1.6 | PRiNS exercises and demos |
exer.3.1.7 | PRiNS exercises and demos |
exer.3.2.1 | PRiNS exercises and demos |
exer.3.2.2 | PRiNS exercises and demos |
exer.3.2.3 | PRiNS exercises and demos |
exer.3.2.4 | PRiNS exercises and demos |
exer.3.2.5 | PRiNS exercises and demos |
exer.3.3.1 | PRiNS exercises and demos |
exer.3.3.2 | PRiNS exercises and demos |
exer.3.3.3 | PRiNS exercises and demos |
exer.3.3.4 | PRiNS exercises and demos |
exer.3.3.5 | PRiNS exercises and demos |
exer.3.3.6 | PRiNS exercises and demos |
exer.4.1.1 | PRiNS exercises and demos |
exer.4.1.2 | PRiNS exercises and demos |
exer.4.1.3 | PRiNS exercises and demos |
exer.4.1.4 | PRiNS exercises and demos |
exer.4.1.5 | PRiNS exercises and demos |
exer.4.1.6 | PRiNS exercises and demos |
exer.4.1.7 | PRiNS exercises and demos |
exer.4.1.8 | PRiNS exercises and demos |
exer.4.1.9 | PRiNS exercises and demos |
exer.4.2.1 | PRiNS exercises and demos |
exer.4.2.2 | PRiNS exercises and demos |
exer.4.2.3 | PRiNS exercises and demos |
exer.4.2.4 | PRiNS exercises and demos |
exer.4.2.5 | PRiNS exercises and demos |
exer.4.2.6 | PRiNS exercises and demos |
exer.4.2.7 | PRiNS exercises and demos |
exer.4.3.1 | PRiNS exercises and demos |
exer.4.3.2 | PRiNS exercises and demos |
exer.4.3.3 | PRiNS exercises and demos |
exer.4.3.4 | PRiNS exercises and demos |
exer.4.3.5 | PRiNS exercises and demos |
exer.4.3.6 | PRiNS exercises and demos |
exer.4.3.7 | PRiNS exercises and demos |
exer.4.3.8 | PRiNS exercises and demos |
exer.4.3.9 | PRiNS exercises and demos |
exer.4.4.1 | PRiNS exercises and demos |
exer.4.4.2 | PRiNS exercises and demos |
exer.4.4.3 | PRiNS exercises and demos |
exer.4.4.4 | PRiNS exercises and demos |
exer.4.4.5 | PRiNS exercises and demos |
exer.4.4.6 | PRiNS exercises and demos |
golub | Subset of a gene expression dataset from Golub et al. (1999) |
golub.cl | Subset of a gene expression dataset from Golub et al. (1999) |
golub.gnames | Subset of a gene expression dataset from Golub et al. (1999) |
grid.2d | Pattern Recognition in the Natural Sciences |
IG_wrong | 30 Near InfraRed (NIR) spectra |
leverage.lims | Analysis of variance - Simultaneous Component Analysis |
loadingplot | Principal Component Analysis plotting functions |
loadings | Principal Component Analysis |
nir.spectra | Near-infrared spectra of ternary mixtures |
NIRdata | 30 Near InfraRed (NIR) spectra |
OptimANN | Pattern Recognition in the Natural Sciences |
OptimSVM | Pattern Recognition in the Natural Sciences |
panel.hist | Pattern Recognition in the Natural Sciences |
PCA | Principal Component Analysis |
PCA.GENES | Analysis of variance - Simultaneous Component Analysis |
PCA.plot | Principal Component Analysis plotting functions |
Plant | Plant data |
plant | Plant data |
pnts2 | Artificial multivariate normal data sets |
pnts5 | Artificial multivariate normal data sets |
PRiNS | Pattern Recognition in the Natural Sciences |
project | Principal Component Analysis |
reconstruct | Principal Component Analysis |
scoreplot | Principal Component Analysis plotting functions |
scores | Principal Component Analysis |
screeplot | Principal Component Analysis plotting functions |
screeplot_asca | Analysis of variance - Simultaneous Component Analysis |
show.var | Analysis of variance - Simultaneous Component Analysis |
simplisma | SIMPle to use Interactive Self-Moddeling Algorithm |
SPE.lims | Analysis of variance - Simultaneous Component Analysis |
spheres | Artificial data sets in three dimensions |
spheres2 | Artificial data sets in three dimensions |
summary.PCA | Principal Component Analysis |
Treatment | Plant data |
Treatments | Plant data |
unsigned.range | Pattern Recognition in the Natural Sciences |
Variables | Plant data |
variances | Principal Component Analysis |
winesLight | Wine data (subset) |
winesLight.classes | Wine data (subset) |
winesLightA | Wine data (subset) |
winesLightA.classes | Wine data (subset) |
winesLightB | Wine data (subset) |
wv | 30 Near InfraRed (NIR) spectra |
X | Plant data |
yeast.alpha | Yeast data: alpha arrestation method |
yeast.alpha.classes | Yeast data: alpha arrestation method |