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/dports/science/py-nilearn/nilearn-0.8.1/examples/04_glm_first_level/
H A Dplot_fir_model.py58 contrasts = dict([(column, contrast_matrix[i]) variable
62 contrasts[condition] = np.sum(
66 contrasts['audio'] = np.sum([contrasts[name] for name in
71 contrasts['video'] = np.sum(
72 [contrasts[name] for name in
78 contrasts['computation'] = contrasts['audio_computation'] +\
80 contrasts['sentences'] = contrasts['sentence_listening'] +\
83 contrasts = { variable
89 'H-V': (contrasts['horizontal_checkerboard'] -
90 contrasts['vertical_checkerboard']),
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H A Dplot_first_level_details.py112 contrasts['audio'] = (
115 + contrasts['audio_computation']
119 contrasts['visual'] = (
122 + contrasts['visual_computation']
123 + contrasts['sentence_reading'])
126 contrasts['computation'] = (contrasts['visual_computation']
130 contrasts['sentences'] = (contrasts['sentence_listening']
134 contrasts = {
141 'audio - visual': contrasts['audio'] - contrasts['visual'],
148 return contrasts
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H A Dplot_fiac_analysis.py86 contrasts = {'SStSSp_minus_DStDSp': pad_vector([1, 0, 0, -1], n_columns), variable
100 for index, (contrast_id, contrast_val) in enumerate(contrasts.items()):
102 index + 1, len(contrasts), contrast_id))
124 contrasts[contrast_id], output_type='z_score')
134 contrasts[contrast_id], output_type='z_score')
144 contrasts[contrast_id], output_type='z_score')
165 contrasts,
/dports/math/R-cran-survey/survey/R/
H A Dregtest.R222 contrasts<-contrasts[,!drop,drop=FALSE]
241 v<-contrasts%*%var%*%t(contrasts)
266 contrasts<-list(contrast=contrasts)
276 contrasts<-match.names(names(coef(stat)),contrasts)
277 contrasts<-do.call(rbind,contrasts)
279 contrasts<-addLin(contrasts, names(coef(stat)))
288 contrasts<-list(contrast=contrasts)
298 contrasts <- match.names(names(coef(stat)), contrasts)
299 contrasts<-do.call(rbind,contrasts)
314 contrasts<-list(contrast=contrasts)
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/dports/math/R/R-4.1.2/src/library/stats/man/
H A Dcontrasts.Rd6 \name{contrasts}
7 \alias{contrasts}
8 \alias{contrasts<-}
14 contrasts(x, contrasts = TRUE, sparse = FALSE)
46 \code{contrasts} (always called with \code{contrasts = TRUE}) and
74 contrasts(fff) # treatment contrasts by default
76 contrasts(fff, contrasts = FALSE) # the 5x5 identity matrix
78 contrasts(fff) <- contr.sum(5); contrasts(fff) # set sum contrasts
79 contrasts(fff, 2) <- contr.sum(5); contrasts(fff) # set 2 contrasts
81 contrasts(fff) <- contr.sum(5)[, 1:2]; contrasts(fff)
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H A Dcontrast.Rd14 Return a matrix of contrasts.
17 contr.helmert(n, contrasts = TRUE, sparse = FALSE)
18 contr.poly(n, scores = 1:n, contrasts = TRUE, sparse = FALSE)
19 contr.sum(n, contrasts = TRUE, sparse = FALSE)
21 contr.SAS(n, contrasts = TRUE, sparse = FALSE)
25 \item{contrasts}{a logical indicating whether contrasts should be
40 computed contrasts. If the argument \code{contrasts} is \code{FALSE}
43 polynomial when \code{contrasts = FALSE}).
49 contrasts}.
68 \code{contrasts} is \code{TRUE} and \code{k=n} if \code{contrasts} is
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H A Dmodel.matrix.Rd15 contrasts.arg = NULL, xlev = NULL, \dots)
22 \item{contrasts.arg}{a list, whose entries are values (numeric
25 as replacement values for the \code{\link{contrasts}}
35 contrasts) and expanding interactions similarly.
48 If \code{contrasts.arg} is specified for a factor it overrides the
49 default factor coding for that variable and any \code{"contrasts"}
50 attribute set by \code{\link{C}} or \code{\link{contrasts}}.
76 specifies the contrasts that would be used in terms in which the
102 model.matrix(~ a + b, dd, contrasts.arg = list(a = "contr.sum"))
106 # invalid contrasts.. ignored with a warning:
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H A Dse.contrast.Rd19 \item{contrast.obj}{The contrasts for which standard errors are
22 the cells to be contrasted. Multiple contrasts should be specified
28 value is the first Helmert contrast, which contrasts the first and
42 In multistratum models, the contrasts can appear in more than one
46 \code{\link{aov}} about using orthogonal contrasts.) Such standard
56 \code{\link{contrasts}}, \code{\link{model.tables}}
68 ## Set suitable contrasts.
69 options(contrasts = c("contr.helmert", "contr.poly"))
96 ## Now look at all three interaction contrasts
118 cont1 <- c(-1, 1)[A]/32 # Helmert contrasts
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/dports/math/libRmath/R-4.1.1/src/library/stats/man/
H A Dcontrasts.Rd6 \name{contrasts}
7 \alias{contrasts}
8 \alias{contrasts<-}
14 contrasts(x, contrasts = TRUE, sparse = FALSE)
46 \code{contrasts} (always called with \code{contrasts = TRUE}) and
74 contrasts(fff) # treatment contrasts by default
76 contrasts(fff, contrasts = FALSE) # the 5x5 identity matrix
78 contrasts(fff) <- contr.sum(5); contrasts(fff) # set sum contrasts
79 contrasts(fff, 2) <- contr.sum(5); contrasts(fff) # set 2 contrasts
81 contrasts(fff) <- contr.sum(5)[, 1:2]; contrasts(fff)
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H A Dcontrast.Rd14 Return a matrix of contrasts.
17 contr.helmert(n, contrasts = TRUE, sparse = FALSE)
18 contr.poly(n, scores = 1:n, contrasts = TRUE, sparse = FALSE)
19 contr.sum(n, contrasts = TRUE, sparse = FALSE)
21 contr.SAS(n, contrasts = TRUE, sparse = FALSE)
25 \item{contrasts}{a logical indicating whether contrasts should be
40 computed contrasts. If the argument \code{contrasts} is \code{FALSE}
43 polynomial when \code{contrasts = FALSE}).
49 contrasts}.
68 \code{contrasts} is \code{TRUE} and \code{k=n} if \code{contrasts} is
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H A Dmodel.matrix.Rd15 contrasts.arg = NULL, xlev = NULL, \dots)
22 \item{contrasts.arg}{a list, whose entries are values (numeric
25 as replacement values for the \code{\link{contrasts}}
35 contrasts) and expanding interactions similarly.
48 If \code{contrasts.arg} is specified for a factor it overrides the
49 default factor coding for that variable and any \code{"contrasts"}
50 attribute set by \code{\link{C}} or \code{\link{contrasts}}.
76 specifies the contrasts that would be used in terms in which the
102 model.matrix(~ a + b, dd, contrasts.arg = list(a = "contr.sum"))
106 # invalid contrasts.. ignored with a warning:
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H A Dse.contrast.Rd19 \item{contrast.obj}{The contrasts for which standard errors are
22 the cells to be contrasted. Multiple contrasts should be specified
28 value is the first Helmert contrast, which contrasts the first and
42 In multistratum models, the contrasts can appear in more than one
46 \code{\link{aov}} about using orthogonal contrasts.) Such standard
56 \code{\link{contrasts}}, \code{\link{model.tables}}
68 ## Set suitable contrasts.
69 options(contrasts = c("contr.helmert", "contr.poly"))
96 ## Now look at all three interaction contrasts
118 cont1 <- c(-1, 1)[A]/32 # Helmert contrasts
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/dports/math/R-cran-memisc/memisc/man/
H A Dcontrasts.Rd5 \alias{contrasts}
8 \alias{contrasts<-}
36 \S4method{contrasts}{item}(x,contrasts=TRUE,\dots)
39 \S4method{contrasts}{ANY}(x,contrasts=TRUE,\dots)
63 \code{contrasts(x)} returns the "contrasts" attribute of an
76 contrasts(x)
78 contrasts(x)
80 contrasts(x)
82 contrasts(x)
91 contrasts(x)
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/dports/devel/R-cran-gmodels/gmodels/man/
H A Dmake.contrasts.Rd3 \name{make.contrasts}
4 \alias{make.contrasts}
10 make.contrasts(contr, how.many = ncol(contr))
31 \code{\link{contrasts}} or to the \code{contrasts} argument of model
51 # Mirror default treatment contrasts
53 lm( y ~ x, contrasts=list(x = test ))
55 # Specify some more complicated contrasts
63 summary(lm( y ~ x, contrasts=list(x=make.contrasts(cmat) )))
65 contrasts(x) <- make.contrasts(cmat)
68 # or use contrasts.lm
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/dports/math/R-cran-memisc/memisc/R/
H A Dcontrasts.R10 args <- list(n=quote(n),...,contrasts=quote(contrasts)) nameattr
11 fun <- function(n,contrasts=TRUE) NULL argument
16 setMethod("contrasts","ANY",function(x,contrasts=TRUE,...)stats::contrasts(x,contrasts=contrasts,..… method
29 if (!contrasts)
36 contrasts = contrasts)
40 contrasts = contrasts)
43 ctr <- ctr(labs,contrasts = contrasts)
113 if (contrasts) {
141 if (contrasts) {
160 contr.sdif <- function (n, contrasts = TRUE) argument
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/dports/math/R-cran-DoE.base/DoE.base/R/
H A Dqua.design.R1 qua.design <- function(design, quantitative=NA, contrasts=character(0), ...){ argument
63 if (length(contrasts)>0){
64 if (length(contrasts)==1) contrasts <- rep(contrasts, di$nfactors)
65 if (length(contrasts)==di$nfactors & is.null(names(contrasts)))
66 names(contrasts) <- names(di$factor.names)
69 if (any(sapply(contrasts, function(obj) !is.function(eval(parse(text=obj))))))
95 contrasts(hilf[,fn[i]]) <- eval(parse(text=paste("contr.poly(",
104 if (fn[i] %in% names(contrasts) | !(fn[i] %in% nowfactors) ){
106 if (!fn[i] %in% names(contrasts)){
124 contrasts(hilf[,fn[i]]) <- eval(parse(text=paste(contrasts[fn[i]],"(",
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/dports/math/R/R-4.1.2/src/library/stats/R/
H A Dcontrast.R21 contrasts <- function (x, contrasts = TRUE, sparse = FALSE) function
26 if(!contrasts)
40 ctrfn(levels(x), contrasts = contrasts, sparse = sparse)
41 else ctrfn(levels(x), contrasts = contrasts)
46 `contrasts<-` <- function(x, how.many, value)
111 function (n, contrasts = TRUE, sparse = FALSE) argument
119 if (contrasts) {
143 if(contrasts) {
164 if (contrasts) {
172 contr.SAS <- function(n, contrasts = TRUE, sparse = FALSE) argument
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/dports/math/libRmath/R-4.1.1/src/library/stats/R/
H A Dcontrast.R21 contrasts <- function (x, contrasts = TRUE, sparse = FALSE) function
26 if(!contrasts)
40 ctrfn(levels(x), contrasts = contrasts, sparse = sparse)
41 else ctrfn(levels(x), contrasts = contrasts)
46 `contrasts<-` <- function(x, how.many, value)
111 function (n, contrasts = TRUE, sparse = FALSE) argument
119 if (contrasts) {
143 if(contrasts) {
164 if (contrasts) {
172 contr.SAS <- function(n, contrasts = TRUE, sparse = FALSE) argument
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/dports/math/R-cran-car/car/man/
H A DContrasts.Rd18 contr.Treatment(n, base = 1, contrasts = TRUE)
20 contr.Sum(n, contrasts = TRUE)
22 contr.Helmert(n, contrasts = TRUE)
28 Ignored if \code{contrasts} is \code{FALSE}.}
29 \item{contrasts}{a logical indicating whether contrasts should be computed.}
35 …The returned value contains the computed contrasts. If the argument \code{contrasts} is \code{FALS…
58 and \code{k = n} if \code{contrasts} is \code{FALSE}.
75 contrasts=list(type="contr.Treatment"))
79 ## contrasts = list(type = "contr.Treatment"))
90 contrasts=list(type="contr.treatment"))
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/dports/math/R-cran-car/car/R/
H A DContrasts.R4 contr.Treatment <- function (n, base = 1, contrasts = TRUE) { argument
15 dec <- if (!contrasts) ""
21 if (contrasts) {
31 contr.Sum <- function (n, contrasts = TRUE) argument
44 dec <- if (!contrasts) ""
49 if (contrasts) {
64 contr.Helmert <- function (n, contrasts = TRUE) argument
77 dec <- if (!contrasts) ""
80 nms <- if (contrasts) 1:lenglev else levels
82 if (contrasts) {
/dports/math/R-cran-DoE.base/DoE.base/man/
H A Dqua.design.Rd12 qua.design(design, quantitative = NA, contrasts = character(0), ...)
13 change.contr(design, contrasts=contr.treatment)
44 or default contrasts.\cr
73 with the default contrasts given below.\cr
75 with treatment contrasts (default) or with custom contrasts as indicated by the
76 \code{contrasts} parameter. \cr
80 The default contrasts for factors in class \code{\link{design}} objects
87 as R factors with treatment contrasts.
95 contrasts (cf. \code{\link[stats:contrast]{contr.treatment}})
115 lm(y~., change.contr(plan)) ## with treatment contrasts instead
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H A Dcontr.FrF2.Rd8 contr.FrF2(n, contrasts=TRUE)
12 \item{n}{ power of 2; number of levels of the factor for which contrasts are
14 \item{contrasts}{must always be \code{TRUE}; option needed for
18 This function mainly supports \code{-1/+1} contrasts for 2-level factors.
24 \value{The function returns orthogonal contrasts for factors with number of levels a power of 2.
27 with 2-level factors are assigned these contrasts, the columns of the model matrix
32 \seealso{ See Also \code{\link[stats]{contrasts}}, \code{\link[FrF2]{FrF2}},
35 ## assign contr.FrF2 contrasts to a factor
37 contrasts(status) <- contr.FrF2(2)
38 contrasts(status)
/dports/math/R-cran-psych/psych/R/
H A Dsim.anova.R5 contrasts <- function(n) { function
15 if(n1) { cont1 <- contrasts(n1)
17 if(n2) {cont2 <- contrasts(n2)
19 IV2 <- rep(outer(rep(1, n1), contrasts(n2)), n/(n2 * n1)) } else {
22 if (n3) {cont3 <- contrasts(n3)
24 IV3 <- rep(outer(rep(1, n1 * n2), contrasts(n3)), n/(n1 * n2 * n3))
25 } else {IV3 <- rep(outer(rep(1, n1 ), contrasts(n3)), n/(n1 * n3))
27 } else {if(n2) {IV3 <- rep(outer(rep(1, n2 ), contrasts(n3)), n/(n2 * n3)) } else {
28 IV3 <- rep(contrasts(n3),n/n3)}
/dports/math/R-cran-FrF2/FrF2/tests/
H A DFrF2test.Rout.save165 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
170 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
175 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
180 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
185 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
190 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
238 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
243 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
248 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
253 ..- attr(*, "contrasts")= num [1:2, 1] -1 1
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/dports/math/R-cran-DoE.base/DoE.base/tests/
H A Dtest_qua.design.R43 qualplan1 <- qua.design(quantplan1, quantitative=NA, contrasts=c(B="contr.treatment"))
46 qualplan2 <- qua.design(quantplan2, quantitative=NA, contrasts=c(B="contr.treatment"))
50 qualplan1 <- qua.design(plan1, quantitative="none", contrasts=c(B="contr.treatment"))
53 qualplan2 <- qua.design(plan2, quantitative="none", contrasts=c(B="contr.treatment"))
57 qualplan1 <- qua.design(quantplan1, quantitative="none", contrasts=c(B="contr.treatment"))
60 qualplan2 <- qua.design(quantplan2, quantitative="none", contrasts=c(B="contr.treatment"))

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