panellipse: Confidence ellipses around products based on panelists...
In SensoMineR: Sensory Data Analysis
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Examples
Description
Virtual panels are generated using Boostrap techniques in order to display
confidence ellipses around products.
Usage
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panellipse(donnee, col.p, col.j, firstvar, lastvar = ncol(donnee),
alpha = 0.05, coord = c(1,2), scale.unit = TRUE, nbsimul = 300,
nbchoix = NULL, group = NULL, name.group = NULL,
level.search.desc = 0.2, centerbypanelist = TRUE,
scalebypanelist = FALSE, name.panelist = FALSE,
variability.variable = TRUE, cex = 1, color = NULL,
graph.type = c("ggplot","classic"))
Arguments
donnee
a data frame made up of at least two qualitative variables
(product, panelist) and a set of quantitative variables (sensory descriptors)
col.p
the position of the product variable
col.j
the position of the panelist variable
firstvar
the position of the first sensory descriptor
lastvar
the position of the last sensory descriptor (by default the last column of donnee)
alpha
the confidence level of the ellipses
coord
a length 2 vector specifying the components to plot
scale.unit
boolean, if T the descriptors are scaled to unit variance
nbsimul
the number of simulations (corresponding to the number of virtual panels) used to compute the ellipses
nbchoix
the number of panelists forming a virtual panel, by default the number of panelists in the original panel
group
the number of variables in each group of variables when multiple factor analysis is performed (by default this parameter equals NULL and a PCA is performed)
name.group
the names of the groups of variables when mfa is performed (if group differs from NULL)
level.search.desc
the threshold above which a descriptor is not considered as discriminant according to AOV model "descriptor=Product+Panelist"
centerbypanelist
boolean, if T center the data by panelist before the construction of the axes
scalebypanelist
boolean, if T scale the data by panelist before the construction of the axes (by default, FALSE
is assigned to that parameter)
name.panelist
boolean, if T then the name of each panelist is displayed on the plotpanelist graph (by default, FALSE
is assigned to that parameter)
variability.variable
boolean, if T a plot with the variability of the variable is drawn and a confidence intervals of the correlations
between descriptors are calculated
cex
cf. function par in the graphics package
color
a vector with the colors used; by default there are 35 colors defined
graph.type
a character that gives the type of graph used: "ggplot" or "classic"
Details
Panellipse, step by step:
Step 1 Performs a selection of discriminating descriptors with respect to a threshold set by users
Step 2 Virtual panels are generated using Boostrap techniques; the number of panels as well as their size
are set by users with the nbsimul and nbchoix parameters
Step 3 Coordinates of the products with respect to each virtual panels are computed
Step 4 Each product is then circled by its confidence ellipse generated by virtual panels and
comprising (1-alpha)*100 percent of the virtual products
Step 5 Variability of the variables is drawn and confidence interval of the correlation coefficient between descriptors are calculated by bootstrap
Value
A list containing the following elements:
eig
a matrix with the component of the factor analysis (in row) and the eigenvalues, the inertia and the cumulative inertia for each component
coordinates
a list with: the coordinates of the products with respect to the panel and to each panelists
and the coordinates of the partial products with respect to the panel and to each panelists
hotelling
Returns a matrix with the P-values of the Hotelling's T2 tests for each pair of products: this matrix allows to find the
product which are significantly different for the 2-components sensory description; if an MFA is done, hotelling returns as many matrices
as there are group, these matrices allows to find the product which are significantly different for the 2-components sensory description of the
group, and it returns also a global matrix corresponding to the P-values for the tests corresponding to the mean product.
correl
a list with: the matrix of the estimated correlation coefficients and two matrices corresponding to the confidence intervals, min and max, of the correlation coefficients calculated by bootstrap.
Returns a graph of the products as well as a correlation circle of the descriptors.
Returns a graph where each product is displayed with respect to a panel and to each panelist composing
the panel; products described by the panel are displayed as square, they are displayed as circle when
they are described by each panelist.
Returns a graph where each product is circled by its confidence ellipse generated by virtual panels.
When a Multiple Factor Analysis is performed, returns a graph where each partial product is circled by its confidence ellipse generated by virtual panels.
Returns a graph where the variability of each variable is drawn on the correlation circle graph.
Author(s)
Francois Husson
References
Husson F., Le Dien S. & Pages J. (2005). Confidence ellipse for the sensory profiles obtained by Principal Components Analysis. Food Quality and Preference. 16 (3), 245-250.
Pages J. & Husson F. (2005). Multiple Factor Analysis with confidence ellipses: a methodology to study the relationships between sensory and instrumental data. To be published in Journal of Chemometrics.
Husson F., Le S. & Pages J. Variability of the representation of the variables resulting from PCA in the case of a conventional sensory profile. Food Quality and Preference. 16 (3), 245-250.
See Also
panellipse.session, panelmatch
Examples
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## Not run:
## Example 1: PCA
data(chocolates)
res <- panellipse(sensochoc, col.p = 4, col.j = 1, firstvar = 5)
coltable(res$hotelling, main.title = "P-values for the Hotelling's T2 tests")
## If we consider only 12 panelists in a virtual panel,
## what would be the size of the ellipses
res2 <- panellipse(sensochoc, col.p = 4, col.j = 1, nbchoix = 12, firstvar = 5)
coltable(res2$hotelling, main.title = "P-values for the Hotelling's T2 tests")
## If we want the confidence ellipses around the individual descriptions
panellipse(sensochoc, col.p = 4, col.j = 1, nbchoix = 1, firstvar = 5)
## Example 2: MFA
data(chocolates)
res <- panellipse(sensochoc, col.p = 4, col.j = 1, firstvar = 5,
group = c(6,8), name.group = c("G1","G2"))
for (i in 1:dim(res$hotelling$bygroup)[3]) coltable(res$hotelling$bygroup[,,i],
main.title = paste("P-values for the Hotelling's T2 tests (",
dimnames(res$hotelling$bygroup)[3][[1]][i],")",sep=""))
## End(Not run)
Example output
Loading required package: FactoMineR
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
dev.new(): using pdf(file="Rplots5.pdf")
dev.new(): using pdf(file="Rplots6.pdf")
dev.new(): using pdf(file="Rplots7.pdf")
dev.new(): using pdf(file="Rplots8.pdf")
dev.new(): using pdf(file="Rplots9.pdf")
dev.new(): using pdf(file="Rplots10.pdf")
dev.new(): using pdf(file="Rplots11.pdf")
dev.new(): using pdf(file="Rplots12.pdf")
dev.new(): using pdf(file="Rplots13.pdf")
$eig
$coordinates
$coordinates$moyen
Dim1 Dim2 Product Panelist
choc1 -3.757796675 1.61821061 choc1 0
choc2 -1.368141617 -0.77976142 choc2 0
choc3 7.479490096 0.65456298 choc3 0
choc4 -1.312132687 0.62686079 choc4 0
choc5 -0.958491687 -0.87373829 choc5 0
choc6 -0.082927430 -1.24613467 choc6 0
i7 -4.933181948 -1.02343349 choc1 1
i8 -0.547308965 2.01556559 choc2 1
i9 6.120010161 0.58513173 choc3 1
i10 -0.200248256 1.07870900 choc4 1
i11 -0.594544015 -1.33943833 choc5 1
i12 0.155273023 -1.31653450 choc6 1
i13 -1.405985464 2.26949264 choc1 2
i14 1.218342057 0.34845613 choc2 2
i15 4.731775422 0.99603403 choc3 2
i16 -0.881604109 -1.58391957 choc4 2
i17 -2.668761176 -0.70527140 choc5 2
i18 -0.993766730 -1.32479183 choc6 2
i19 -5.573914361 2.62087610 choc1 3
i20 -0.847765087 -1.15405408 choc2 3
i21 8.505752718 -0.12704964 choc3 3
i22 -1.510385300 -0.12068956 choc4 3
i23 -2.493491422 -0.79294245 choc5 3
i24 1.919803452 -0.42614038 choc6 3
i25 -5.937089968 -0.11016574 choc1 4
i26 -1.822390188 -3.51761531 choc2 4
i27 11.899206837 -1.72977191 choc3 4
i28 -4.386287342 1.44126313 choc4 4
i29 2.547811630 3.80606226 choc5 4
i30 -2.301250969 0.11022758 choc6 4
i31 -5.207902568 1.88113730 choc1 5
i32 1.324317897 -1.43171526 choc2 5
i33 4.376936695 1.90519194 choc3 5
i34 -3.924059034 -1.45660541 choc4 5
i35 0.005035789 0.37956548 choc5 5
i36 3.425671221 -1.27757406 choc6 5
i37 -0.211501472 1.98437333 choc1 6
i38 -1.581831166 0.79639220 choc2 6
i39 1.527242976 -2.42173424 choc3 6
i40 -0.976850109 0.73160923 choc4 6
i41 -1.183671502 -2.58145115 choc5 6
i42 2.426611273 1.49081063 choc6 6
i43 -0.485455212 3.87047992 choc1 7
i44 -1.868352887 -1.59593252 choc2 7
i45 5.268262725 -0.95862133 choc3 7
i46 1.228724715 0.44372940 choc4 7
i47 -4.112760653 1.79023315 choc5 7
i48 -0.030418688 -3.54988863 choc6 7
i49 -0.751844785 4.18891995 choc1 8
i50 -6.071779542 -1.26735726 choc2 8
i51 12.720493632 4.09268884 choc3 8
i52 -2.299060742 -0.29219326 choc4 8
i53 -1.341976427 -3.85713122 choc5 8
i54 -2.255832137 -2.86492705 choc6 8
i55 -6.692501469 3.86900150 choc1 9
i56 -5.822883739 -2.93217898 choc2 9
i57 10.472771095 0.97216003 choc3 9
i58 2.068375167 2.59676017 choc4 9
i59 1.768253217 -1.26616686 choc5 9
i60 -1.794014271 -3.23957585 choc6 9
i61 -4.713119355 0.32641044 choc1 10
i62 1.158050468 -0.07514870 choc2 10
i63 6.541603422 1.24894965 choc3 10
i64 -1.947150701 2.27868307 choc4 10
i65 -1.828643913 -2.10452703 choc5 10
i66 0.789260080 -1.67436744 choc6 10
i67 -3.303180585 -0.69738512 choc1 11
i68 -0.407648515 -0.36691627 choc2 11
i69 6.840100989 1.95567073 choc3 11
i70 -1.672708667 1.01419273 choc4 11
i71 0.643369360 1.04026281 choc5 11
i72 -2.099932582 -2.94582487 choc6 11
i73 -5.173620443 -0.70340215 choc1 12
i74 -1.161636290 -1.09028522 choc2 12
i75 8.894182214 3.21676207 choc3 12
i76 -3.233499033 0.24955708 choc4 12
i77 0.688819247 -1.23073453 choc5 12
i78 -0.014245695 -0.44189725 choc6 12
i79 -0.216202434 2.92179520 choc1 13
i80 -1.951535557 -1.10964584 choc2 13
i81 9.416167401 -0.53596302 choc3 13
i82 -2.118456569 1.89815735 choc4 13
i83 -3.527717195 -1.00910840 choc5 13
i84 -1.602255646 -2.16523529 choc6 13
i85 -1.018440678 2.82833486 choc1 14
i86 -0.750021327 -0.88597333 choc2 14
i87 3.490351145 -0.43446759 choc3 14
i88 -0.271288997 -1.32378856 choc4 14
i89 0.728105418 0.20875568 choc5 14
i90 -2.178705561 -0.39286106 choc6 14
i91 -3.912748154 0.85954362 choc1 15
i92 -4.108068768 -0.06525563 choc2 15
i93 8.271858967 0.96919425 choc3 15
i94 -1.136983749 1.52043877 choc4 15
i95 2.573755805 -0.83141800 choc5 15
i96 -1.687814102 -2.45250301 choc6 15
i97 -6.748800003 -0.46759770 choc1 16
i98 -0.051481170 -3.64613359 choc2 16
i99 7.938068116 1.57469878 choc3 16
i100 0.770978082 4.55004683 choc4 16
i101 -3.699086044 -0.33649101 choc5 16
i102 1.790321019 -1.67452330 choc6 16
i103 -1.841443127 4.04716039 choc1 17
i104 -4.081366067 -0.61712579 choc2 17
i105 10.544601496 -0.85265555 choc3 17
i106 -1.846471959 2.56190705 choc4 17
i107 -3.044267704 -3.53210449 choc5 17
i108 0.268947361 -1.60718161 choc6 17
i109 -3.697666113 4.55382619 choc1 18
i110 -0.425241284 -0.77867829 choc2 18
i111 8.458894570 0.98847636 choc3 18
i112 -4.917650536 -0.93477660 choc4 18
i113 -0.093062174 -1.30015607 choc5 18
i114 0.674725537 -2.52869159 choc6 18
i115 -4.147214125 1.73705785 choc1 19
i116 1.914807663 -0.84580023 choc2 19
i117 5.030477738 0.92006718 choc3 19
i118 -1.395248093 1.02286574 choc4 19
i119 -1.739174253 -2.93016404 choc5 19
i120 0.336351070 0.09597350 choc6 19
i121 -4.440827539 0.21966682 choc1 20
i122 -1.128950907 1.51693044 choc2 20
i123 13.455601989 1.96975294 choc3 20
i124 -7.265626525 -0.12721380 choc4 20
i125 -2.632087856 0.43499907 choc5 20
i126 2.011890837 -4.01413548 choc6 20
i127 -3.006115326 2.79661727 choc1 21
i128 -0.685202680 -0.03784867 choc2 21
i129 5.943115571 -0.19388140 choc3 21
i130 -1.178776701 1.33613752 choc4 21
i131 -0.544751305 -1.48559444 choc5 21
i132 -0.528269559 -2.41543028 choc6 21
i133 -5.764187837 -0.04399262 choc1 22
i134 -1.259913459 -1.81753926 choc2 22
i135 8.904448667 3.89857791 choc3 22
i136 -1.170682746 0.67368206 choc4 22
i137 0.689242508 -1.33580395 choc5 22
i138 -1.398907134 -1.37492413 choc6 22
i139 -3.420764458 1.39566301 choc1 23
i140 -1.035256203 -0.92313134 choc2 23
i141 7.552161831 0.63666339 choc3 23
i142 -1.737639087 -0.02525798 choc4 23
i143 -0.534404724 -0.91293604 choc5 23
i144 -0.824097359 -0.17100104 choc6 23
i145 -6.461528420 -0.14155122 choc1 24
i146 -0.167033953 -0.69327071 choc2 24
i147 9.585189637 0.27050901 choc3 24
i148 -0.245652014 1.38261166 choc4 24
i149 -3.342541290 -2.20001863 choc5 24
i150 0.631566039 1.38171988 choc6 24
i151 -1.206503984 2.06142039 choc1 25
i152 0.402029428 1.08162280 choc2 25
i153 2.481729446 0.13925542 choc3 25
i154 -2.380923385 -1.87312173 choc4 25
i155 1.522456954 -1.73197433 choc5 25
i156 -0.818788459 0.32279744 choc6 25
i157 -4.335951469 -0.17396537 choc1 26
i158 -2.850971389 -0.26161754 choc2 26
i159 5.985979244 0.59466080 choc3 26
i160 1.000218317 -1.06971170 choc4 26
i161 -0.244140358 0.12573927 choc5 26
i162 0.444865654 0.78489454 choc6 26
i163 -2.707969905 1.04211646 choc1 27
i164 0.584938515 -0.82974489 choc2 27
i165 2.437278727 -0.51998878 choc3 27
i166 -1.142523778 0.51383108 choc4 27
i167 -1.104530848 0.14634487 choc5 27
i168 1.932807289 -0.35255874 choc6 27
i169 -5.284286585 3.33666805 choc1 28
i170 -2.028833641 -0.68212730 choc2 28
i171 12.103806962 1.68328169 choc3 28
i172 -0.047856303 -0.24538082 choc4 28
i173 -3.070243300 -2.70694676 choc5 28
i174 -1.672587133 -1.38549486 choc6 28
i175 -6.376155793 1.47903977 choc1 29
i176 -5.623120131 -1.74695226 choc2 29
i177 7.407142391 -1.86126702 choc3 29
i178 4.767489527 1.93744000 choc4 29
i179 -1.163252702 0.92000615 choc5 29
i180 0.987896708 -0.72826664 choc6 29
$coordinates$eig
eigenvalue percentage of variance cumulative percentage of variance
comp 1 12.43048248 88.7891606 88.78916
comp 2 1.06071846 7.5765605 96.36572
comp 3 0.37251599 2.6608285 99.02655
comp 4 0.09570998 0.6836427 99.71019
comp 5 0.04057308 0.2898077 100.00000
$coordinates$plotInd
$graph
$graph$plotInd
$graph$plotVar
$graph$plotIndEll
$graph$plotPan
$graph$plotVarVariab
$correl
$correl$moy
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.0000000 -0.9643480 0.9785248 -0.9571752 -0.9360588 -0.9879772
MilkA -0.9643480 1.0000000 -0.9936930 0.9921083 0.9811928 0.9630937
CocoaF 0.9785248 -0.9936930 1.0000000 -0.9861461 -0.9831321 -0.9849654
MilkF -0.9571752 0.9921083 -0.9861461 1.0000000 0.9901273 0.9629777
Caramel -0.9360588 0.9811928 -0.9831321 0.9901273 1.0000000 0.9606128
Vanilla -0.9879772 0.9630937 -0.9849654 0.9629777 0.9606128 1.0000000
Sweetness -0.8832588 0.9609963 -0.9598773 0.9467762 0.9714737 0.9127383
Acidity 0.8178182 -0.9051651 0.9078363 -0.8822963 -0.9226157 -0.8493130
Bitterness 0.9380061 -0.9726131 0.9840980 -0.9561170 -0.9744724 -0.9589034
Astringency 0.8830144 -0.9412720 0.9519673 -0.9236238 -0.9572212 -0.9140783
Crunchy 0.8042928 -0.7731539 0.7567830 -0.8221982 -0.7579852 -0.7810121
Melting -0.8614261 0.8689393 -0.8532705 0.9166081 0.8795951 0.8507954
Sticky -0.9168947 0.8218217 -0.8278757 0.8050145 0.7378884 0.8489268
Granular 0.8956231 -0.9432427 0.9308954 -0.9681953 -0.9612149 -0.8981823
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA -0.8832588 0.8178182 0.9380061 0.8830144 0.8042928 -0.8614261
MilkA 0.9609963 -0.9051651 -0.9726131 -0.9412720 -0.7731539 0.8689393
CocoaF -0.9598773 0.9078363 0.9840980 0.9519673 0.7567830 -0.8532705
MilkF 0.9467762 -0.8822963 -0.9561170 -0.9236238 -0.8221982 0.9166081
Caramel 0.9714737 -0.9226157 -0.9744724 -0.9572212 -0.7579852 0.8795951
Vanilla 0.9127383 -0.8493130 -0.9589034 -0.9140783 -0.7810121 0.8507954
Sweetness 1.0000000 -0.9796763 -0.9859952 -0.9899582 -0.6027099 0.7540383
Acidity -0.9796763 1.0000000 0.9624395 0.9897819 0.4594500 -0.6608026
Bitterness -0.9859952 0.9624395 1.0000000 0.9898841 0.6352927 -0.7710618
Astringency -0.9899582 0.9897819 0.9898841 1.0000000 0.5461241 -0.7187801
Crunchy -0.6027099 0.4594500 0.6352927 0.5461241 1.0000000 -0.9465937
Melting 0.7540383 -0.6608026 -0.7710618 -0.7187801 -0.9465937 1.0000000
Sticky 0.6546969 -0.5807156 -0.7444366 -0.6579702 -0.7933640 0.7859009
Granular -0.9006487 0.8591927 0.9018204 0.8857045 0.8046914 -0.9452493
Sticky Granular
CocoaA -0.9168947 0.8956231
MilkA 0.8218217 -0.9432427
CocoaF -0.8278757 0.9308954
MilkF 0.8050145 -0.9681953
Caramel 0.7378884 -0.9612149
Vanilla 0.8489268 -0.8981823
Sweetness 0.6546969 -0.9006487
Acidity -0.5807156 0.8591927
Bitterness -0.7444366 0.9018204
Astringency -0.6579702 0.8857045
Crunchy -0.7933640 0.8046914
Melting 0.7859009 -0.9452493
Sticky 1.0000000 -0.7520919
Granular -0.7520919 1.0000000
$correl$mini
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.00000000 -0.9850601 -0.08667191 -0.9914515 -0.9896497 -0.9180195
MilkA -0.98506014 1.0000000 -0.98869344 -0.2811128 -0.6302949 -0.2340823
CocoaF -0.08667191 -0.9886934 1.00000000 -0.9902238 -0.9590431 -0.9840464
MilkF -0.99145153 -0.2811128 -0.99022383 1.0000000 -0.3675383 -0.6109057
Caramel -0.98964975 -0.6302949 -0.95904309 -0.3675383 1.0000000 -0.3180859
Vanilla -0.91801953 -0.2340823 -0.98404638 -0.6109057 -0.3180859 1.0000000
Sweetness -0.94178300 -0.9328719 -0.96824802 -0.4535349 -0.5760275 -0.1142080
Acidity -0.64820372 -0.8613764 -0.48020543 -0.8851157 -0.9631062 -0.9641930
Bitterness -0.61868822 -0.9615995 0.15322185 -0.9595140 -0.9066552 -0.9563821
Astringency -0.48911599 -0.8855603 -0.61732708 -0.9331752 -0.9965008 -0.7980075
Crunchy -0.44250405 -0.8421949 0.00000000 -0.9754262 -0.9779015 -0.8663692
Melting -0.93961848 -0.7590179 -0.92157759 -0.5656854 -0.3967957 -0.3689726
Sticky -0.87533500 -0.3544588 -0.94106465 -0.7657097 -0.7484552 -0.5773503
Granular -0.79166667 -0.9522509 -0.81569940 -0.9160035 -0.8776919 -0.8478419
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA -0.9417830 -0.6482037 -0.6186882 -0.4891160 -0.4425040 -0.9396185
MilkA -0.9328719 -0.8613764 -0.9615995 -0.8855603 -0.8421949 -0.7590179
CocoaF -0.9682480 -0.4802054 0.1532218 -0.6173271 0.0000000 -0.9215776
MilkF -0.4535349 -0.8851157 -0.9595140 -0.9331752 -0.9754262 -0.5656854
Caramel -0.5760275 -0.9631062 -0.9066552 -0.9965008 -0.9779015 -0.3967957
Vanilla -0.1142080 -0.9641930 -0.9563821 -0.7980075 -0.8663692 -0.3689726
Sweetness 1.0000000 -0.9480515 -0.9791622 -0.9621509 -0.8696827 -0.4082483
Acidity -0.9480515 1.0000000 -0.4054991 -0.7329220 -0.5330018 -0.7951535
Bitterness -0.9791622 -0.4054991 1.0000000 -0.6398319 -0.1337203 -0.9416472
Astringency -0.9621509 -0.7329220 -0.6398319 1.0000000 -0.6752825 -0.8174239
Crunchy -0.8696827 -0.5330018 -0.1337203 -0.6752825 1.0000000 -0.9840627
Melting -0.4082483 -0.7951535 -0.9416472 -0.8174239 -0.9840627 1.0000000
Sticky -0.8411582 -0.6418523 -0.9383275 -0.8798420 -0.9870335 -0.8625819
Granular -0.9672759 -0.4695048 -0.7280440 -0.6629233 -0.6650835 -0.9610923
Sticky Granular
CocoaA -0.8753350 -0.7916667
MilkA -0.3544588 -0.9522509
CocoaF -0.9410647 -0.8156994
MilkF -0.7657097 -0.9160035
Caramel -0.7484552 -0.8776919
Vanilla -0.5773503 -0.8478419
Sweetness -0.8411582 -0.9672759
Acidity -0.6418523 -0.4695048
Bitterness -0.9383275 -0.7280440
Astringency -0.8798420 -0.6629233
Crunchy -0.9870335 -0.6650835
Melting -0.8625819 -0.9610923
Sticky 1.0000000 -0.8575054
Granular -0.8575054 1.0000000
$correl$maxi
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.0000000 0.4554433 0.95768612 0.2082717 2.939419e-01 NA
MilkA 0.4554433 1.0000000 0.56719209 0.9869834 8.909181e-01 NA
CocoaF 0.9576861 0.5671921 1.00000000 -0.2693429 -3.252463e-01 NA
MilkF 0.2082717 0.9869834 -0.26934285 1.0000000 9.874414e-01 NA
Caramel 0.2939419 0.8909181 -0.32524625 0.9874414 1.000000e+00 NA
Vanilla NA NA NA NA NA 1
Sweetness 0.3859225 0.9193304 -0.02335709 0.9937416 9.826212e-01 NA
Acidity 0.8879400 0.9389530 0.90403070 0.3656536 2.725022e-01 NA
Bitterness 0.8882702 0.4571760 0.97733221 -0.3859499 -2.207241e-01 NA
Astringency 0.9375812 0.5158770 0.95755740 0.7121722 3.080181e-01 NA
Crunchy 0.9278844 0.4110901 0.89536932 -0.1000927 4.474284e-01 NA
Melting 0.8146131 0.9745830 0.60395717 0.9780595 9.004503e-01 NA
Sticky 0.4264014 0.8433383 0.60569788 0.8764222 8.707793e-01 NA
Granular 0.9496528 0.6787421 0.93831394 0.4242641 7.697702e-21 NA
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA 0.38592249 0.8879400 0.8882702 0.9375812 0.9278844 0.8146131
MilkA 0.91933042 0.9389530 0.4571760 0.5158770 0.4110901 0.9745830
CocoaF -0.02335709 0.9040307 0.9773322 0.9575574 0.8953693 0.6039572
MilkF 0.99374158 0.3656536 -0.3859499 0.7121722 -0.1000927 0.9780595
Caramel 0.98262120 0.2725022 -0.2207241 0.3080181 0.4474284 0.9004503
Vanilla NA NA NA NA NA NA
Sweetness 1.00000000 0.3872983 -0.1546721 0.6661737 0.2436549 0.9002417
Acidity 0.38729833 1.0000000 0.9514617 0.9800277 0.7977240 0.3643931
Bitterness -0.15467206 0.9514617 1.0000000 0.9888193 0.8656605 0.4892615
Astringency 0.66617372 0.9800277 0.9888193 1.0000000 0.9020123 0.8759182
Crunchy 0.24365493 0.7977240 0.8656605 0.9020123 1.0000000 0.4926646
Melting 0.90024169 0.3643931 0.4892615 0.8759182 0.4926646 1.0000000
Sticky 0.93265158 0.8246211 0.9349876 0.8926074 0.2446610 0.8341775
Granular 0.60132003 0.8955228 0.9468286 0.8972335 0.7842289 0.2991162
Sticky Granular
CocoaA 0.4264014 9.496528e-01
MilkA 0.8433383 6.787421e-01
CocoaF 0.6056979 9.383139e-01
MilkF 0.8764222 4.242641e-01
Caramel 0.8707793 7.697702e-21
Vanilla NA NA
Sweetness 0.9326516 6.013200e-01
Acidity 0.8246211 8.955228e-01
Bitterness 0.9349876 9.468286e-01
Astringency 0.8926074 8.972335e-01
Crunchy 0.2446610 7.842289e-01
Melting 0.8341775 2.991162e-01
Sticky 1.0000000 7.715114e-01
Granular 0.7715114 1.000000e+00
There were 50 or more warnings (use warnings() to see the first 50)
dev.new(): using pdf(file="Rplots14.pdf")
dev.new(): using pdf(file="Rplots15.pdf")
dev.new(): using pdf(file="Rplots16.pdf")
dev.new(): using pdf(file="Rplots17.pdf")
dev.new(): using pdf(file="Rplots18.pdf")
dev.new(): using pdf(file="Rplots19.pdf")
dev.new(): using pdf(file="Rplots20.pdf")
dev.new(): using pdf(file="Rplots21.pdf")
SensoMineR documentation built on July 2, 2020, 1:56 a.m.
R Package Documentation
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Description Usage Arguments Details Value Author(s) References See Also Examples
Description
Virtual panels are generated using Boostrap techniques in order to display confidence ellipses around products.
Usage
1 2 3 4 5 6 7 | panellipse(donnee, col.p, col.j, firstvar, lastvar = ncol(donnee),
alpha = 0.05, coord = c(1,2), scale.unit = TRUE, nbsimul = 300,
nbchoix = NULL, group = NULL, name.group = NULL,
level.search.desc = 0.2, centerbypanelist = TRUE,
scalebypanelist = FALSE, name.panelist = FALSE,
variability.variable = TRUE, cex = 1, color = NULL,
graph.type = c("ggplot","classic"))
|
Arguments
donnee |
a data frame made up of at least two qualitative variables (product, panelist) and a set of quantitative variables (sensory descriptors) |
col.p |
the position of the product variable |
col.j |
the position of the panelist variable |
firstvar |
the position of the first sensory descriptor |
lastvar |
the position of the last sensory descriptor (by default the last column of |
alpha |
the confidence level of the ellipses |
coord |
a length 2 vector specifying the components to plot |
scale.unit |
boolean, if T the descriptors are scaled to unit variance |
nbsimul |
the number of simulations (corresponding to the number of virtual panels) used to compute the ellipses |
nbchoix |
the number of panelists forming a virtual panel, by default the number of panelists in the original panel |
group |
the number of variables in each group of variables when multiple factor analysis is performed (by default this parameter equals NULL and a PCA is performed) |
name.group |
the names of the groups of variables when mfa is performed (if |
level.search.desc |
the threshold above which a descriptor is not considered as discriminant according to AOV model |
centerbypanelist |
boolean, if T center the data by panelist before the construction of the axes |
scalebypanelist |
boolean, if T scale the data by panelist before the construction of the axes (by default, FALSE is assigned to that parameter) |
name.panelist |
boolean, if T then the name of each panelist is displayed on the |
variability.variable |
boolean, if T a plot with the variability of the variable is drawn and a confidence intervals of the correlations between descriptors are calculated |
cex |
cf. function |
color |
a vector with the colors used; by default there are 35 colors defined |
graph.type |
a character that gives the type of graph used: "ggplot" or "classic" |
Details
Panellipse, step by step:
Step 1 Performs a selection of discriminating descriptors with respect to a threshold set by users
Step 2 Virtual panels are generated using Boostrap techniques; the number of panels as well as their size
are set by users with the nbsimul and nbchoix parameters
Step 3 Coordinates of the products with respect to each virtual panels are computed
Step 4 Each product is then circled by its confidence ellipse generated by virtual panels and
comprising (1-alpha)*100 percent of the virtual products
Step 5 Variability of the variables is drawn and confidence interval of the correlation coefficient between descriptors are calculated by bootstrap
Value
A list containing the following elements:
eig |
a matrix with the component of the factor analysis (in row) and the eigenvalues, the inertia and the cumulative inertia for each component |
coordinates |
a list with: the coordinates of the products with respect to the panel and to each panelists and the coordinates of the partial products with respect to the panel and to each panelists |
hotelling |
Returns a matrix with the P-values of the Hotelling's T2 tests for each pair of products: this matrix allows to find the product which are significantly different for the 2-components sensory description; if an MFA is done, hotelling returns as many matrices as there are group, these matrices allows to find the product which are significantly different for the 2-components sensory description of the group, and it returns also a global matrix corresponding to the P-values for the tests corresponding to the mean product. |
correl |
a list with: the matrix of the estimated correlation coefficients and two matrices corresponding to the confidence intervals, min and max, of the correlation coefficients calculated by bootstrap. |
Returns a graph of the products as well as a correlation circle of the descriptors.
Returns a graph where each product is displayed with respect to a panel and to each panelist composing
the panel; products described by the panel are displayed as square, they are displayed as circle when
they are described by each panelist.
Returns a graph where each product is circled by its confidence ellipse generated by virtual panels.
When a Multiple Factor Analysis is performed, returns a graph where each partial product is circled by its confidence ellipse generated by virtual panels.
Returns a graph where the variability of each variable is drawn on the correlation circle graph.
Author(s)
Francois Husson
References
Husson F., Le Dien S. & Pages J. (2005). Confidence ellipse for the sensory profiles obtained by Principal Components Analysis. Food Quality and Preference. 16 (3), 245-250.
Pages J. & Husson F. (2005). Multiple Factor Analysis with confidence ellipses: a methodology to study the relationships between sensory and instrumental data. To be published in Journal of Chemometrics.
Husson F., Le S. & Pages J. Variability of the representation of the variables resulting from PCA in the case of a conventional sensory profile. Food Quality and Preference. 16 (3), 245-250.
See Also
panellipse.session, panelmatch
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Not run:
## Example 1: PCA
data(chocolates)
res <- panellipse(sensochoc, col.p = 4, col.j = 1, firstvar = 5)
coltable(res$hotelling, main.title = "P-values for the Hotelling's T2 tests")
## If we consider only 12 panelists in a virtual panel,
## what would be the size of the ellipses
res2 <- panellipse(sensochoc, col.p = 4, col.j = 1, nbchoix = 12, firstvar = 5)
coltable(res2$hotelling, main.title = "P-values for the Hotelling's T2 tests")
## If we want the confidence ellipses around the individual descriptions
panellipse(sensochoc, col.p = 4, col.j = 1, nbchoix = 1, firstvar = 5)
## Example 2: MFA
data(chocolates)
res <- panellipse(sensochoc, col.p = 4, col.j = 1, firstvar = 5,
group = c(6,8), name.group = c("G1","G2"))
for (i in 1:dim(res$hotelling$bygroup)[3]) coltable(res$hotelling$bygroup[,,i],
main.title = paste("P-values for the Hotelling's T2 tests (",
dimnames(res$hotelling$bygroup)[3][[1]][i],")",sep=""))
## End(Not run)
|
Example output
Loading required package: FactoMineR
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
dev.new(): using pdf(file="Rplots5.pdf")
dev.new(): using pdf(file="Rplots6.pdf")
dev.new(): using pdf(file="Rplots7.pdf")
dev.new(): using pdf(file="Rplots8.pdf")
dev.new(): using pdf(file="Rplots9.pdf")
dev.new(): using pdf(file="Rplots10.pdf")
dev.new(): using pdf(file="Rplots11.pdf")
dev.new(): using pdf(file="Rplots12.pdf")
dev.new(): using pdf(file="Rplots13.pdf")
$eig
$coordinates
$coordinates$moyen
Dim1 Dim2 Product Panelist
choc1 -3.757796675 1.61821061 choc1 0
choc2 -1.368141617 -0.77976142 choc2 0
choc3 7.479490096 0.65456298 choc3 0
choc4 -1.312132687 0.62686079 choc4 0
choc5 -0.958491687 -0.87373829 choc5 0
choc6 -0.082927430 -1.24613467 choc6 0
i7 -4.933181948 -1.02343349 choc1 1
i8 -0.547308965 2.01556559 choc2 1
i9 6.120010161 0.58513173 choc3 1
i10 -0.200248256 1.07870900 choc4 1
i11 -0.594544015 -1.33943833 choc5 1
i12 0.155273023 -1.31653450 choc6 1
i13 -1.405985464 2.26949264 choc1 2
i14 1.218342057 0.34845613 choc2 2
i15 4.731775422 0.99603403 choc3 2
i16 -0.881604109 -1.58391957 choc4 2
i17 -2.668761176 -0.70527140 choc5 2
i18 -0.993766730 -1.32479183 choc6 2
i19 -5.573914361 2.62087610 choc1 3
i20 -0.847765087 -1.15405408 choc2 3
i21 8.505752718 -0.12704964 choc3 3
i22 -1.510385300 -0.12068956 choc4 3
i23 -2.493491422 -0.79294245 choc5 3
i24 1.919803452 -0.42614038 choc6 3
i25 -5.937089968 -0.11016574 choc1 4
i26 -1.822390188 -3.51761531 choc2 4
i27 11.899206837 -1.72977191 choc3 4
i28 -4.386287342 1.44126313 choc4 4
i29 2.547811630 3.80606226 choc5 4
i30 -2.301250969 0.11022758 choc6 4
i31 -5.207902568 1.88113730 choc1 5
i32 1.324317897 -1.43171526 choc2 5
i33 4.376936695 1.90519194 choc3 5
i34 -3.924059034 -1.45660541 choc4 5
i35 0.005035789 0.37956548 choc5 5
i36 3.425671221 -1.27757406 choc6 5
i37 -0.211501472 1.98437333 choc1 6
i38 -1.581831166 0.79639220 choc2 6
i39 1.527242976 -2.42173424 choc3 6
i40 -0.976850109 0.73160923 choc4 6
i41 -1.183671502 -2.58145115 choc5 6
i42 2.426611273 1.49081063 choc6 6
i43 -0.485455212 3.87047992 choc1 7
i44 -1.868352887 -1.59593252 choc2 7
i45 5.268262725 -0.95862133 choc3 7
i46 1.228724715 0.44372940 choc4 7
i47 -4.112760653 1.79023315 choc5 7
i48 -0.030418688 -3.54988863 choc6 7
i49 -0.751844785 4.18891995 choc1 8
i50 -6.071779542 -1.26735726 choc2 8
i51 12.720493632 4.09268884 choc3 8
i52 -2.299060742 -0.29219326 choc4 8
i53 -1.341976427 -3.85713122 choc5 8
i54 -2.255832137 -2.86492705 choc6 8
i55 -6.692501469 3.86900150 choc1 9
i56 -5.822883739 -2.93217898 choc2 9
i57 10.472771095 0.97216003 choc3 9
i58 2.068375167 2.59676017 choc4 9
i59 1.768253217 -1.26616686 choc5 9
i60 -1.794014271 -3.23957585 choc6 9
i61 -4.713119355 0.32641044 choc1 10
i62 1.158050468 -0.07514870 choc2 10
i63 6.541603422 1.24894965 choc3 10
i64 -1.947150701 2.27868307 choc4 10
i65 -1.828643913 -2.10452703 choc5 10
i66 0.789260080 -1.67436744 choc6 10
i67 -3.303180585 -0.69738512 choc1 11
i68 -0.407648515 -0.36691627 choc2 11
i69 6.840100989 1.95567073 choc3 11
i70 -1.672708667 1.01419273 choc4 11
i71 0.643369360 1.04026281 choc5 11
i72 -2.099932582 -2.94582487 choc6 11
i73 -5.173620443 -0.70340215 choc1 12
i74 -1.161636290 -1.09028522 choc2 12
i75 8.894182214 3.21676207 choc3 12
i76 -3.233499033 0.24955708 choc4 12
i77 0.688819247 -1.23073453 choc5 12
i78 -0.014245695 -0.44189725 choc6 12
i79 -0.216202434 2.92179520 choc1 13
i80 -1.951535557 -1.10964584 choc2 13
i81 9.416167401 -0.53596302 choc3 13
i82 -2.118456569 1.89815735 choc4 13
i83 -3.527717195 -1.00910840 choc5 13
i84 -1.602255646 -2.16523529 choc6 13
i85 -1.018440678 2.82833486 choc1 14
i86 -0.750021327 -0.88597333 choc2 14
i87 3.490351145 -0.43446759 choc3 14
i88 -0.271288997 -1.32378856 choc4 14
i89 0.728105418 0.20875568 choc5 14
i90 -2.178705561 -0.39286106 choc6 14
i91 -3.912748154 0.85954362 choc1 15
i92 -4.108068768 -0.06525563 choc2 15
i93 8.271858967 0.96919425 choc3 15
i94 -1.136983749 1.52043877 choc4 15
i95 2.573755805 -0.83141800 choc5 15
i96 -1.687814102 -2.45250301 choc6 15
i97 -6.748800003 -0.46759770 choc1 16
i98 -0.051481170 -3.64613359 choc2 16
i99 7.938068116 1.57469878 choc3 16
i100 0.770978082 4.55004683 choc4 16
i101 -3.699086044 -0.33649101 choc5 16
i102 1.790321019 -1.67452330 choc6 16
i103 -1.841443127 4.04716039 choc1 17
i104 -4.081366067 -0.61712579 choc2 17
i105 10.544601496 -0.85265555 choc3 17
i106 -1.846471959 2.56190705 choc4 17
i107 -3.044267704 -3.53210449 choc5 17
i108 0.268947361 -1.60718161 choc6 17
i109 -3.697666113 4.55382619 choc1 18
i110 -0.425241284 -0.77867829 choc2 18
i111 8.458894570 0.98847636 choc3 18
i112 -4.917650536 -0.93477660 choc4 18
i113 -0.093062174 -1.30015607 choc5 18
i114 0.674725537 -2.52869159 choc6 18
i115 -4.147214125 1.73705785 choc1 19
i116 1.914807663 -0.84580023 choc2 19
i117 5.030477738 0.92006718 choc3 19
i118 -1.395248093 1.02286574 choc4 19
i119 -1.739174253 -2.93016404 choc5 19
i120 0.336351070 0.09597350 choc6 19
i121 -4.440827539 0.21966682 choc1 20
i122 -1.128950907 1.51693044 choc2 20
i123 13.455601989 1.96975294 choc3 20
i124 -7.265626525 -0.12721380 choc4 20
i125 -2.632087856 0.43499907 choc5 20
i126 2.011890837 -4.01413548 choc6 20
i127 -3.006115326 2.79661727 choc1 21
i128 -0.685202680 -0.03784867 choc2 21
i129 5.943115571 -0.19388140 choc3 21
i130 -1.178776701 1.33613752 choc4 21
i131 -0.544751305 -1.48559444 choc5 21
i132 -0.528269559 -2.41543028 choc6 21
i133 -5.764187837 -0.04399262 choc1 22
i134 -1.259913459 -1.81753926 choc2 22
i135 8.904448667 3.89857791 choc3 22
i136 -1.170682746 0.67368206 choc4 22
i137 0.689242508 -1.33580395 choc5 22
i138 -1.398907134 -1.37492413 choc6 22
i139 -3.420764458 1.39566301 choc1 23
i140 -1.035256203 -0.92313134 choc2 23
i141 7.552161831 0.63666339 choc3 23
i142 -1.737639087 -0.02525798 choc4 23
i143 -0.534404724 -0.91293604 choc5 23
i144 -0.824097359 -0.17100104 choc6 23
i145 -6.461528420 -0.14155122 choc1 24
i146 -0.167033953 -0.69327071 choc2 24
i147 9.585189637 0.27050901 choc3 24
i148 -0.245652014 1.38261166 choc4 24
i149 -3.342541290 -2.20001863 choc5 24
i150 0.631566039 1.38171988 choc6 24
i151 -1.206503984 2.06142039 choc1 25
i152 0.402029428 1.08162280 choc2 25
i153 2.481729446 0.13925542 choc3 25
i154 -2.380923385 -1.87312173 choc4 25
i155 1.522456954 -1.73197433 choc5 25
i156 -0.818788459 0.32279744 choc6 25
i157 -4.335951469 -0.17396537 choc1 26
i158 -2.850971389 -0.26161754 choc2 26
i159 5.985979244 0.59466080 choc3 26
i160 1.000218317 -1.06971170 choc4 26
i161 -0.244140358 0.12573927 choc5 26
i162 0.444865654 0.78489454 choc6 26
i163 -2.707969905 1.04211646 choc1 27
i164 0.584938515 -0.82974489 choc2 27
i165 2.437278727 -0.51998878 choc3 27
i166 -1.142523778 0.51383108 choc4 27
i167 -1.104530848 0.14634487 choc5 27
i168 1.932807289 -0.35255874 choc6 27
i169 -5.284286585 3.33666805 choc1 28
i170 -2.028833641 -0.68212730 choc2 28
i171 12.103806962 1.68328169 choc3 28
i172 -0.047856303 -0.24538082 choc4 28
i173 -3.070243300 -2.70694676 choc5 28
i174 -1.672587133 -1.38549486 choc6 28
i175 -6.376155793 1.47903977 choc1 29
i176 -5.623120131 -1.74695226 choc2 29
i177 7.407142391 -1.86126702 choc3 29
i178 4.767489527 1.93744000 choc4 29
i179 -1.163252702 0.92000615 choc5 29
i180 0.987896708 -0.72826664 choc6 29
$coordinates$eig
eigenvalue percentage of variance cumulative percentage of variance
comp 1 12.43048248 88.7891606 88.78916
comp 2 1.06071846 7.5765605 96.36572
comp 3 0.37251599 2.6608285 99.02655
comp 4 0.09570998 0.6836427 99.71019
comp 5 0.04057308 0.2898077 100.00000
$coordinates$plotInd
$graph
$graph$plotInd
$graph$plotVar
$graph$plotIndEll
$graph$plotPan
$graph$plotVarVariab
$correl
$correl$moy
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.0000000 -0.9643480 0.9785248 -0.9571752 -0.9360588 -0.9879772
MilkA -0.9643480 1.0000000 -0.9936930 0.9921083 0.9811928 0.9630937
CocoaF 0.9785248 -0.9936930 1.0000000 -0.9861461 -0.9831321 -0.9849654
MilkF -0.9571752 0.9921083 -0.9861461 1.0000000 0.9901273 0.9629777
Caramel -0.9360588 0.9811928 -0.9831321 0.9901273 1.0000000 0.9606128
Vanilla -0.9879772 0.9630937 -0.9849654 0.9629777 0.9606128 1.0000000
Sweetness -0.8832588 0.9609963 -0.9598773 0.9467762 0.9714737 0.9127383
Acidity 0.8178182 -0.9051651 0.9078363 -0.8822963 -0.9226157 -0.8493130
Bitterness 0.9380061 -0.9726131 0.9840980 -0.9561170 -0.9744724 -0.9589034
Astringency 0.8830144 -0.9412720 0.9519673 -0.9236238 -0.9572212 -0.9140783
Crunchy 0.8042928 -0.7731539 0.7567830 -0.8221982 -0.7579852 -0.7810121
Melting -0.8614261 0.8689393 -0.8532705 0.9166081 0.8795951 0.8507954
Sticky -0.9168947 0.8218217 -0.8278757 0.8050145 0.7378884 0.8489268
Granular 0.8956231 -0.9432427 0.9308954 -0.9681953 -0.9612149 -0.8981823
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA -0.8832588 0.8178182 0.9380061 0.8830144 0.8042928 -0.8614261
MilkA 0.9609963 -0.9051651 -0.9726131 -0.9412720 -0.7731539 0.8689393
CocoaF -0.9598773 0.9078363 0.9840980 0.9519673 0.7567830 -0.8532705
MilkF 0.9467762 -0.8822963 -0.9561170 -0.9236238 -0.8221982 0.9166081
Caramel 0.9714737 -0.9226157 -0.9744724 -0.9572212 -0.7579852 0.8795951
Vanilla 0.9127383 -0.8493130 -0.9589034 -0.9140783 -0.7810121 0.8507954
Sweetness 1.0000000 -0.9796763 -0.9859952 -0.9899582 -0.6027099 0.7540383
Acidity -0.9796763 1.0000000 0.9624395 0.9897819 0.4594500 -0.6608026
Bitterness -0.9859952 0.9624395 1.0000000 0.9898841 0.6352927 -0.7710618
Astringency -0.9899582 0.9897819 0.9898841 1.0000000 0.5461241 -0.7187801
Crunchy -0.6027099 0.4594500 0.6352927 0.5461241 1.0000000 -0.9465937
Melting 0.7540383 -0.6608026 -0.7710618 -0.7187801 -0.9465937 1.0000000
Sticky 0.6546969 -0.5807156 -0.7444366 -0.6579702 -0.7933640 0.7859009
Granular -0.9006487 0.8591927 0.9018204 0.8857045 0.8046914 -0.9452493
Sticky Granular
CocoaA -0.9168947 0.8956231
MilkA 0.8218217 -0.9432427
CocoaF -0.8278757 0.9308954
MilkF 0.8050145 -0.9681953
Caramel 0.7378884 -0.9612149
Vanilla 0.8489268 -0.8981823
Sweetness 0.6546969 -0.9006487
Acidity -0.5807156 0.8591927
Bitterness -0.7444366 0.9018204
Astringency -0.6579702 0.8857045
Crunchy -0.7933640 0.8046914
Melting 0.7859009 -0.9452493
Sticky 1.0000000 -0.7520919
Granular -0.7520919 1.0000000
$correl$mini
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.00000000 -0.9850601 -0.08667191 -0.9914515 -0.9896497 -0.9180195
MilkA -0.98506014 1.0000000 -0.98869344 -0.2811128 -0.6302949 -0.2340823
CocoaF -0.08667191 -0.9886934 1.00000000 -0.9902238 -0.9590431 -0.9840464
MilkF -0.99145153 -0.2811128 -0.99022383 1.0000000 -0.3675383 -0.6109057
Caramel -0.98964975 -0.6302949 -0.95904309 -0.3675383 1.0000000 -0.3180859
Vanilla -0.91801953 -0.2340823 -0.98404638 -0.6109057 -0.3180859 1.0000000
Sweetness -0.94178300 -0.9328719 -0.96824802 -0.4535349 -0.5760275 -0.1142080
Acidity -0.64820372 -0.8613764 -0.48020543 -0.8851157 -0.9631062 -0.9641930
Bitterness -0.61868822 -0.9615995 0.15322185 -0.9595140 -0.9066552 -0.9563821
Astringency -0.48911599 -0.8855603 -0.61732708 -0.9331752 -0.9965008 -0.7980075
Crunchy -0.44250405 -0.8421949 0.00000000 -0.9754262 -0.9779015 -0.8663692
Melting -0.93961848 -0.7590179 -0.92157759 -0.5656854 -0.3967957 -0.3689726
Sticky -0.87533500 -0.3544588 -0.94106465 -0.7657097 -0.7484552 -0.5773503
Granular -0.79166667 -0.9522509 -0.81569940 -0.9160035 -0.8776919 -0.8478419
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA -0.9417830 -0.6482037 -0.6186882 -0.4891160 -0.4425040 -0.9396185
MilkA -0.9328719 -0.8613764 -0.9615995 -0.8855603 -0.8421949 -0.7590179
CocoaF -0.9682480 -0.4802054 0.1532218 -0.6173271 0.0000000 -0.9215776
MilkF -0.4535349 -0.8851157 -0.9595140 -0.9331752 -0.9754262 -0.5656854
Caramel -0.5760275 -0.9631062 -0.9066552 -0.9965008 -0.9779015 -0.3967957
Vanilla -0.1142080 -0.9641930 -0.9563821 -0.7980075 -0.8663692 -0.3689726
Sweetness 1.0000000 -0.9480515 -0.9791622 -0.9621509 -0.8696827 -0.4082483
Acidity -0.9480515 1.0000000 -0.4054991 -0.7329220 -0.5330018 -0.7951535
Bitterness -0.9791622 -0.4054991 1.0000000 -0.6398319 -0.1337203 -0.9416472
Astringency -0.9621509 -0.7329220 -0.6398319 1.0000000 -0.6752825 -0.8174239
Crunchy -0.8696827 -0.5330018 -0.1337203 -0.6752825 1.0000000 -0.9840627
Melting -0.4082483 -0.7951535 -0.9416472 -0.8174239 -0.9840627 1.0000000
Sticky -0.8411582 -0.6418523 -0.9383275 -0.8798420 -0.9870335 -0.8625819
Granular -0.9672759 -0.4695048 -0.7280440 -0.6629233 -0.6650835 -0.9610923
Sticky Granular
CocoaA -0.8753350 -0.7916667
MilkA -0.3544588 -0.9522509
CocoaF -0.9410647 -0.8156994
MilkF -0.7657097 -0.9160035
Caramel -0.7484552 -0.8776919
Vanilla -0.5773503 -0.8478419
Sweetness -0.8411582 -0.9672759
Acidity -0.6418523 -0.4695048
Bitterness -0.9383275 -0.7280440
Astringency -0.8798420 -0.6629233
Crunchy -0.9870335 -0.6650835
Melting -0.8625819 -0.9610923
Sticky 1.0000000 -0.8575054
Granular -0.8575054 1.0000000
$correl$maxi
CocoaA MilkA CocoaF MilkF Caramel Vanilla
CocoaA 1.0000000 0.4554433 0.95768612 0.2082717 2.939419e-01 NA
MilkA 0.4554433 1.0000000 0.56719209 0.9869834 8.909181e-01 NA
CocoaF 0.9576861 0.5671921 1.00000000 -0.2693429 -3.252463e-01 NA
MilkF 0.2082717 0.9869834 -0.26934285 1.0000000 9.874414e-01 NA
Caramel 0.2939419 0.8909181 -0.32524625 0.9874414 1.000000e+00 NA
Vanilla NA NA NA NA NA 1
Sweetness 0.3859225 0.9193304 -0.02335709 0.9937416 9.826212e-01 NA
Acidity 0.8879400 0.9389530 0.90403070 0.3656536 2.725022e-01 NA
Bitterness 0.8882702 0.4571760 0.97733221 -0.3859499 -2.207241e-01 NA
Astringency 0.9375812 0.5158770 0.95755740 0.7121722 3.080181e-01 NA
Crunchy 0.9278844 0.4110901 0.89536932 -0.1000927 4.474284e-01 NA
Melting 0.8146131 0.9745830 0.60395717 0.9780595 9.004503e-01 NA
Sticky 0.4264014 0.8433383 0.60569788 0.8764222 8.707793e-01 NA
Granular 0.9496528 0.6787421 0.93831394 0.4242641 7.697702e-21 NA
Sweetness Acidity Bitterness Astringency Crunchy Melting
CocoaA 0.38592249 0.8879400 0.8882702 0.9375812 0.9278844 0.8146131
MilkA 0.91933042 0.9389530 0.4571760 0.5158770 0.4110901 0.9745830
CocoaF -0.02335709 0.9040307 0.9773322 0.9575574 0.8953693 0.6039572
MilkF 0.99374158 0.3656536 -0.3859499 0.7121722 -0.1000927 0.9780595
Caramel 0.98262120 0.2725022 -0.2207241 0.3080181 0.4474284 0.9004503
Vanilla NA NA NA NA NA NA
Sweetness 1.00000000 0.3872983 -0.1546721 0.6661737 0.2436549 0.9002417
Acidity 0.38729833 1.0000000 0.9514617 0.9800277 0.7977240 0.3643931
Bitterness -0.15467206 0.9514617 1.0000000 0.9888193 0.8656605 0.4892615
Astringency 0.66617372 0.9800277 0.9888193 1.0000000 0.9020123 0.8759182
Crunchy 0.24365493 0.7977240 0.8656605 0.9020123 1.0000000 0.4926646
Melting 0.90024169 0.3643931 0.4892615 0.8759182 0.4926646 1.0000000
Sticky 0.93265158 0.8246211 0.9349876 0.8926074 0.2446610 0.8341775
Granular 0.60132003 0.8955228 0.9468286 0.8972335 0.7842289 0.2991162
Sticky Granular
CocoaA 0.4264014 9.496528e-01
MilkA 0.8433383 6.787421e-01
CocoaF 0.6056979 9.383139e-01
MilkF 0.8764222 4.242641e-01
Caramel 0.8707793 7.697702e-21
Vanilla NA NA
Sweetness 0.9326516 6.013200e-01
Acidity 0.8246211 8.955228e-01
Bitterness 0.9349876 9.468286e-01
Astringency 0.8926074 8.972335e-01
Crunchy 0.2446610 7.842289e-01
Melting 0.8341775 2.991162e-01
Sticky 1.0000000 7.715114e-01
Granular 0.7715114 1.000000e+00
There were 50 or more warnings (use warnings() to see the first 50)
dev.new(): using pdf(file="Rplots14.pdf")
dev.new(): using pdf(file="Rplots15.pdf")
dev.new(): using pdf(file="Rplots16.pdf")
dev.new(): using pdf(file="Rplots17.pdf")
dev.new(): using pdf(file="Rplots18.pdf")
dev.new(): using pdf(file="Rplots19.pdf")
dev.new(): using pdf(file="Rplots20.pdf")
dev.new(): using pdf(file="Rplots21.pdf")
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