/dports/science/py-nilearn/nilearn-0.8.1/examples/04_glm_first_level/ |
H A D | plot_fir_model.py | 58 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']), [all …]
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H A D | plot_first_level_details.py | 112 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 [all …]
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H A D | plot_fiac_analysis.py | 86 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,
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/dports/math/R-cran-survey/survey/R/ |
H A D | regtest.R | 222 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) [all …]
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/dports/math/R/R-4.1.2/src/library/stats/man/ |
H A D | contrasts.Rd | 6 \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) [all …]
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H A D | contrast.Rd | 14 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 [all …]
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H A D | model.matrix.Rd | 15 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: [all …]
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H A D | se.contrast.Rd | 19 \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 [all …]
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/dports/math/libRmath/R-4.1.1/src/library/stats/man/ |
H A D | contrasts.Rd | 6 \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) [all …]
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H A D | contrast.Rd | 14 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 [all …]
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H A D | model.matrix.Rd | 15 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: [all …]
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H A D | se.contrast.Rd | 19 \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 [all …]
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/dports/math/R-cran-memisc/memisc/man/ |
H A D | contrasts.Rd | 5 \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) [all …]
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/dports/devel/R-cran-gmodels/gmodels/man/ |
H A D | make.contrasts.Rd | 3 \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 [all …]
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/dports/math/R-cran-memisc/memisc/R/ |
H A D | contrasts.R | 10 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 [all …]
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/dports/math/R-cran-DoE.base/DoE.base/R/ |
H A D | qua.design.R | 1 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]],"(", [all …]
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/dports/math/R/R-4.1.2/src/library/stats/R/ |
H A D | contrast.R | 21 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 [all …]
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/dports/math/libRmath/R-4.1.1/src/library/stats/R/ |
H A D | contrast.R | 21 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 [all …]
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/dports/math/R-cran-car/car/man/ |
H A D | Contrasts.Rd | 18 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")) [all …]
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/dports/math/R-cran-car/car/R/ |
H A D | Contrasts.R | 4 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) {
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/dports/math/R-cran-DoE.base/DoE.base/man/ |
H A D | qua.design.Rd | 12 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 [all …]
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H A D | contr.FrF2.Rd | 8 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)
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/dports/math/R-cran-psych/psych/R/ |
H A D | sim.anova.R | 5 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)}
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/dports/math/R-cran-FrF2/FrF2/tests/ |
H A D | FrF2test.Rout.save | 165 ..- 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 [all …]
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/dports/math/R-cran-DoE.base/DoE.base/tests/ |
H A D | test_qua.design.R | 43 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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