R/disc.h.R
In hyunsooseol/snowCluster: Multivariate Analysis
Defines functions
disc
Documented in
disc
# This file is automatically generated, you probably don't want to edit this
discOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
covs = NULL,
per = 1,
prior = TRUE,
gm = FALSE,
coef = FALSE,
nl = FALSE,
prop = FALSE,
tra = FALSE,
tes = FALSE,
gc = TRUE,
plot = FALSE,
plot1 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500, ...) {
super$initialize(
package="snowCluster",
name="disc",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..per <- jmvcore::OptionNumber$new(
"per",
per,
min=0.1,
max=1,
default=1)
private$..prior <- jmvcore::OptionBool$new(
"prior",
prior,
default=TRUE)
private$..gm <- jmvcore::OptionBool$new(
"gm",
gm,
default=FALSE)
private$..coef <- jmvcore::OptionBool$new(
"coef",
coef,
default=FALSE)
private$..nl <- jmvcore::OptionBool$new(
"nl",
nl,
default=FALSE)
private$..prop <- jmvcore::OptionBool$new(
"prop",
prop,
default=FALSE)
private$..tra <- jmvcore::OptionBool$new(
"tra",
tra,
default=FALSE)
private$..tes <- jmvcore::OptionBool$new(
"tes",
tes,
default=FALSE)
private$..gc <- jmvcore::OptionBool$new(
"gc",
gc,
default=TRUE)
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=FALSE)
private$..plot1 <- jmvcore::OptionBool$new(
"plot1",
plot1,
default=FALSE)
private$..width <- jmvcore::OptionInteger$new(
"width",
width,
default=500)
private$..height <- jmvcore::OptionInteger$new(
"height",
height,
default=500)
private$..width1 <- jmvcore::OptionInteger$new(
"width1",
width1,
default=500)
private$..height1 <- jmvcore::OptionInteger$new(
"height1",
height1,
default=500)
self$.addOption(private$..dep)
self$.addOption(private$..covs)
self$.addOption(private$..per)
self$.addOption(private$..prior)
self$.addOption(private$..gm)
self$.addOption(private$..coef)
self$.addOption(private$..nl)
self$.addOption(private$..prop)
self$.addOption(private$..tra)
self$.addOption(private$..tes)
self$.addOption(private$..gc)
self$.addOption(private$..plot)
self$.addOption(private$..plot1)
self$.addOption(private$..width)
self$.addOption(private$..height)
self$.addOption(private$..width1)
self$.addOption(private$..height1)
}),
active = list(
dep = function() private$..dep$value,
covs = function() private$..covs$value,
per = function() private$..per$value,
prior = function() private$..prior$value,
gm = function() private$..gm$value,
coef = function() private$..coef$value,
nl = function() private$..nl$value,
prop = function() private$..prop$value,
tra = function() private$..tra$value,
tes = function() private$..tes$value,
gc = function() private$..gc$value,
plot = function() private$..plot$value,
plot1 = function() private$..plot1$value,
width = function() private$..width$value,
height = function() private$..height$value,
width1 = function() private$..width1$value,
height1 = function() private$..height1$value),
private = list(
..dep = NA,
..covs = NA,
..per = NA,
..prior = NA,
..gm = NA,
..coef = NA,
..nl = NA,
..prop = NA,
..tra = NA,
..tes = NA,
..gc = NA,
..plot = NA,
..plot1 = NA,
..width = NA,
..height = NA,
..width1 = NA,
..height1 = NA)
)
discResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discResults",
inherit = jmvcore::Group,
active = list(
instructions = function() private$.items[["instructions"]],
text = function() private$.items[["text"]],
prior = function() private$.items[["prior"]],
gm = function() private$.items[["gm"]],
coef = function() private$.items[["coef"]],
nl = function() private$.items[["nl"]],
prop = function() private$.items[["prop"]],
tra = function() private$.items[["tra"]],
tes = function() private$.items[["tes"]],
plot = function() private$.items[["plot"]],
gc = function() private$.items[["gc"]],
plot1 = function() private$.items[["plot1"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Linear Discriminant Analysis",
refs="snowCluster")
self$add(jmvcore::Html$new(
options=options,
name="instructions",
title="Instructions",
visible=TRUE))
self$add(jmvcore::Preformatted$new(
options=options,
name="text",
title=" "))
self$add(jmvcore::Table$new(
options=options,
name="prior",
title="Prior probability of groups",
visible="(prior)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"),
list(
`name`="value",
`title`="Value"))))
self$add(jmvcore::Table$new(
options=options,
name="gm",
title="Group means",
visible="(gm)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="coef",
title="Coefficients of linear discriminants",
refs="MASS",
visible="(coef)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="nl",
title="Normalized loadings",
refs="MASS",
visible="(nl)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="prop",
title="Proportion of trace",
visible="(prop)",
rows=1,
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="Proportion(%)"),
list(
`name`="LD1",
`type`="number"),
list(
`name`="LD2",
`type`="number"))))
self$add(jmvcore::Table$new(
options=options,
name="tra",
title="Confusion matrix with training set",
visible="(tra)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="tes",
title="Confusion matrix with test set",
visible="(tes)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Linear discriminant plot",
requiresData=TRUE,
visible="(plot)",
renderFun=".plot",
clearWith=list(
"covs",
"dep",
"per",
"width",
"height")))
self$add(jmvcore::Table$new(
options=options,
name="gc",
title="Group centroids",
refs="MASS",
visible="(gc)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="Groups",
`type`="text",
`content`="($key)"),
list(
`name`="ld1",
`title`="LD1",
`type`="number"),
list(
`name`="ld2",
`title`="LD2",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plot1",
title="Histogram",
requiresData=TRUE,
visible="(plot1)",
renderFun=".plot1",
clearWith=list(
"covs",
"dep",
"per",
"width1",
"height1")))}))
discBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "snowCluster",
name = "disc",
version = c(1,0,0),
options = options,
results = discResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Linear Discriminant Analysis
#'
#'
#' @param data .
#' @param dep .
#' @param covs .
#' @param per .
#' @param prior .
#' @param gm .
#' @param coef .
#' @param nl .
#' @param prop .
#' @param tra .
#' @param tes .
#' @param gc .
#' @param plot .
#' @param plot1 .
#' @param width .
#' @param height .
#' @param width1 .
#' @param height1 .
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$instructions} \tab \tab \tab \tab \tab a html \cr
#' \code{results$text} \tab \tab \tab \tab \tab a preformatted \cr
#' \code{results$prior} \tab \tab \tab \tab \tab a table \cr
#' \code{results$gm} \tab \tab \tab \tab \tab a table \cr
#' \code{results$coef} \tab \tab \tab \tab \tab a table \cr
#' \code{results$nl} \tab \tab \tab \tab \tab a table \cr
#' \code{results$prop} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tra} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tes} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$gc} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot1} \tab \tab \tab \tab \tab an image \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$prior$asDF}
#'
#' \code{as.data.frame(results$prior)}
#'
#' @export
disc <- function(
data,
dep,
covs,
per = 1,
prior = TRUE,
gm = FALSE,
coef = FALSE,
nl = FALSE,
prop = FALSE,
tra = FALSE,
tes = FALSE,
gc = TRUE,
plot = FALSE,
plot1 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("disc requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(covs)) covs <- jmvcore::resolveQuo(jmvcore::enquo(covs))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(covs), covs, NULL))
for (v in dep) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- discOptions$new(
dep = dep,
covs = covs,
per = per,
prior = prior,
gm = gm,
coef = coef,
nl = nl,
prop = prop,
tra = tra,
tes = tes,
gc = gc,
plot = plot,
plot1 = plot1,
width = width,
height = height,
width1 = width1,
height1 = height1)
analysis <- discClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
hyunsooseol/snowCluster documentation built on April 5, 2025, 2:06 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions disc
Documented in disc
# This file is automatically generated, you probably don't want to edit this
discOptions <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discOptions",
inherit = jmvcore::Options,
public = list(
initialize = function(
dep = NULL,
covs = NULL,
per = 1,
prior = TRUE,
gm = FALSE,
coef = FALSE,
nl = FALSE,
prop = FALSE,
tra = FALSE,
tes = FALSE,
gc = TRUE,
plot = FALSE,
plot1 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500, ...) {
super$initialize(
package="snowCluster",
name="disc",
requiresData=TRUE,
...)
private$..dep <- jmvcore::OptionVariable$new(
"dep",
dep,
suggested=list(
"nominal"),
permitted=list(
"factor"))
private$..covs <- jmvcore::OptionVariables$new(
"covs",
covs,
suggested=list(
"continuous"),
permitted=list(
"numeric"))
private$..per <- jmvcore::OptionNumber$new(
"per",
per,
min=0.1,
max=1,
default=1)
private$..prior <- jmvcore::OptionBool$new(
"prior",
prior,
default=TRUE)
private$..gm <- jmvcore::OptionBool$new(
"gm",
gm,
default=FALSE)
private$..coef <- jmvcore::OptionBool$new(
"coef",
coef,
default=FALSE)
private$..nl <- jmvcore::OptionBool$new(
"nl",
nl,
default=FALSE)
private$..prop <- jmvcore::OptionBool$new(
"prop",
prop,
default=FALSE)
private$..tra <- jmvcore::OptionBool$new(
"tra",
tra,
default=FALSE)
private$..tes <- jmvcore::OptionBool$new(
"tes",
tes,
default=FALSE)
private$..gc <- jmvcore::OptionBool$new(
"gc",
gc,
default=TRUE)
private$..plot <- jmvcore::OptionBool$new(
"plot",
plot,
default=FALSE)
private$..plot1 <- jmvcore::OptionBool$new(
"plot1",
plot1,
default=FALSE)
private$..width <- jmvcore::OptionInteger$new(
"width",
width,
default=500)
private$..height <- jmvcore::OptionInteger$new(
"height",
height,
default=500)
private$..width1 <- jmvcore::OptionInteger$new(
"width1",
width1,
default=500)
private$..height1 <- jmvcore::OptionInteger$new(
"height1",
height1,
default=500)
self$.addOption(private$..dep)
self$.addOption(private$..covs)
self$.addOption(private$..per)
self$.addOption(private$..prior)
self$.addOption(private$..gm)
self$.addOption(private$..coef)
self$.addOption(private$..nl)
self$.addOption(private$..prop)
self$.addOption(private$..tra)
self$.addOption(private$..tes)
self$.addOption(private$..gc)
self$.addOption(private$..plot)
self$.addOption(private$..plot1)
self$.addOption(private$..width)
self$.addOption(private$..height)
self$.addOption(private$..width1)
self$.addOption(private$..height1)
}),
active = list(
dep = function() private$..dep$value,
covs = function() private$..covs$value,
per = function() private$..per$value,
prior = function() private$..prior$value,
gm = function() private$..gm$value,
coef = function() private$..coef$value,
nl = function() private$..nl$value,
prop = function() private$..prop$value,
tra = function() private$..tra$value,
tes = function() private$..tes$value,
gc = function() private$..gc$value,
plot = function() private$..plot$value,
plot1 = function() private$..plot1$value,
width = function() private$..width$value,
height = function() private$..height$value,
width1 = function() private$..width1$value,
height1 = function() private$..height1$value),
private = list(
..dep = NA,
..covs = NA,
..per = NA,
..prior = NA,
..gm = NA,
..coef = NA,
..nl = NA,
..prop = NA,
..tra = NA,
..tes = NA,
..gc = NA,
..plot = NA,
..plot1 = NA,
..width = NA,
..height = NA,
..width1 = NA,
..height1 = NA)
)
discResults <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discResults",
inherit = jmvcore::Group,
active = list(
instructions = function() private$.items[["instructions"]],
text = function() private$.items[["text"]],
prior = function() private$.items[["prior"]],
gm = function() private$.items[["gm"]],
coef = function() private$.items[["coef"]],
nl = function() private$.items[["nl"]],
prop = function() private$.items[["prop"]],
tra = function() private$.items[["tra"]],
tes = function() private$.items[["tes"]],
plot = function() private$.items[["plot"]],
gc = function() private$.items[["gc"]],
plot1 = function() private$.items[["plot1"]]),
private = list(),
public=list(
initialize=function(options) {
super$initialize(
options=options,
name="",
title="Linear Discriminant Analysis",
refs="snowCluster")
self$add(jmvcore::Html$new(
options=options,
name="instructions",
title="Instructions",
visible=TRUE))
self$add(jmvcore::Preformatted$new(
options=options,
name="text",
title=" "))
self$add(jmvcore::Table$new(
options=options,
name="prior",
title="Prior probability of groups",
visible="(prior)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"),
list(
`name`="value",
`title`="Value"))))
self$add(jmvcore::Table$new(
options=options,
name="gm",
title="Group means",
visible="(gm)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="coef",
title="Coefficients of linear discriminants",
refs="MASS",
visible="(coef)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="nl",
title="Normalized loadings",
refs="MASS",
visible="(nl)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="prop",
title="Proportion of trace",
visible="(prop)",
rows=1,
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="Proportion(%)"),
list(
`name`="LD1",
`type`="number"),
list(
`name`="LD2",
`type`="number"))))
self$add(jmvcore::Table$new(
options=options,
name="tra",
title="Confusion matrix with training set",
visible="(tra)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Table$new(
options=options,
name="tes",
title="Confusion matrix with test set",
visible="(tes)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="",
`type`="text",
`content`="($key)"))))
self$add(jmvcore::Image$new(
options=options,
name="plot",
title="Linear discriminant plot",
requiresData=TRUE,
visible="(plot)",
renderFun=".plot",
clearWith=list(
"covs",
"dep",
"per",
"width",
"height")))
self$add(jmvcore::Table$new(
options=options,
name="gc",
title="Group centroids",
refs="MASS",
visible="(gc)",
clearWith=list(
"covs",
"dep",
"per"),
columns=list(
list(
`name`="name",
`title`="Groups",
`type`="text",
`content`="($key)"),
list(
`name`="ld1",
`title`="LD1",
`type`="number"),
list(
`name`="ld2",
`title`="LD2",
`type`="number"))))
self$add(jmvcore::Image$new(
options=options,
name="plot1",
title="Histogram",
requiresData=TRUE,
visible="(plot1)",
renderFun=".plot1",
clearWith=list(
"covs",
"dep",
"per",
"width1",
"height1")))}))
discBase <- if (requireNamespace("jmvcore", quietly=TRUE)) R6::R6Class(
"discBase",
inherit = jmvcore::Analysis,
public = list(
initialize = function(options, data=NULL, datasetId="", analysisId="", revision=0) {
super$initialize(
package = "snowCluster",
name = "disc",
version = c(1,0,0),
options = options,
results = discResults$new(options=options),
data = data,
datasetId = datasetId,
analysisId = analysisId,
revision = revision,
pause = NULL,
completeWhenFilled = FALSE,
requiresMissings = FALSE,
weightsSupport = 'auto')
}))
#' Linear Discriminant Analysis
#'
#'
#' @param data .
#' @param dep .
#' @param covs .
#' @param per .
#' @param prior .
#' @param gm .
#' @param coef .
#' @param nl .
#' @param prop .
#' @param tra .
#' @param tes .
#' @param gc .
#' @param plot .
#' @param plot1 .
#' @param width .
#' @param height .
#' @param width1 .
#' @param height1 .
#' @return A results object containing:
#' \tabular{llllll}{
#' \code{results$instructions} \tab \tab \tab \tab \tab a html \cr
#' \code{results$text} \tab \tab \tab \tab \tab a preformatted \cr
#' \code{results$prior} \tab \tab \tab \tab \tab a table \cr
#' \code{results$gm} \tab \tab \tab \tab \tab a table \cr
#' \code{results$coef} \tab \tab \tab \tab \tab a table \cr
#' \code{results$nl} \tab \tab \tab \tab \tab a table \cr
#' \code{results$prop} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tra} \tab \tab \tab \tab \tab a table \cr
#' \code{results$tes} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot} \tab \tab \tab \tab \tab an image \cr
#' \code{results$gc} \tab \tab \tab \tab \tab a table \cr
#' \code{results$plot1} \tab \tab \tab \tab \tab an image \cr
#' }
#'
#' Tables can be converted to data frames with \code{asDF} or \code{\link{as.data.frame}}. For example:
#'
#' \code{results$prior$asDF}
#'
#' \code{as.data.frame(results$prior)}
#'
#' @export
disc <- function(
data,
dep,
covs,
per = 1,
prior = TRUE,
gm = FALSE,
coef = FALSE,
nl = FALSE,
prop = FALSE,
tra = FALSE,
tes = FALSE,
gc = TRUE,
plot = FALSE,
plot1 = FALSE,
width = 500,
height = 500,
width1 = 500,
height1 = 500) {
if ( ! requireNamespace("jmvcore", quietly=TRUE))
stop("disc requires jmvcore to be installed (restart may be required)")
if ( ! missing(dep)) dep <- jmvcore::resolveQuo(jmvcore::enquo(dep))
if ( ! missing(covs)) covs <- jmvcore::resolveQuo(jmvcore::enquo(covs))
if (missing(data))
data <- jmvcore::marshalData(
parent.frame(),
`if`( ! missing(dep), dep, NULL),
`if`( ! missing(covs), covs, NULL))
for (v in dep) if (v %in% names(data)) data[[v]] <- as.factor(data[[v]])
options <- discOptions$new(
dep = dep,
covs = covs,
per = per,
prior = prior,
gm = gm,
coef = coef,
nl = nl,
prop = prop,
tra = tra,
tes = tes,
gc = gc,
plot = plot,
plot1 = plot1,
width = width,
height = height,
width1 = width1,
height1 = height1)
analysis <- discClass$new(
options = options,
data = data)
analysis$run()
analysis$results
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.