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StatisticResults_PCA_mdatools Class

Source: R/class_StatisticResults_PCA_mdatools.R
StatisticResults_PCA_mdatools.Rd

The StatisticResults_PCA_mdatools class is used to store results of PCA model created with the mdatools package.

Usage

StatisticResults_PCA_mdatools(model = list())

# S3 method for class 'StatisticResults_PCA_mdatools'
validate_object(x)

# S3 method for class 'StatisticResults_PCA_mdatools'
summary(object, ...)

# S3 method for class 'StatisticResults_PCA_mdatools'
get_model_data(x)

# S3 method for class 'StatisticResults_PCA_mdatools'
predict(x, data)

# S3 method for class 'StatisticResults_PCA_mdatools'
test(x, data)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_explained_variance(
  x,
  interactive = TRUE,
  xLab = NULL,
  yLab = NULL,
  title = NULL,
  showText = TRUE,
  showLegend = TRUE
)

# S3 method for class 'StatisticResults_Model'
plot_cumulative_explained_variance(
  x,
  interactive = TRUE,
  xLab = NULL,
  yLab = NULL,
  title = NULL,
  showText = TRUE,
  showLegend = TRUE
)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_scores(
  x,
  analyses = NULL,
  interactive = TRUE,
  pcs = 1:2,
  title = NULL,
  colorGroups = NULL,
  showText = TRUE,
  showLegend = TRUE,
  colorBy = "results"
)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_loadings(
  x,
  interactive = TRUE,
  pcs = 1:2,
  colorKey = NULL,
  title = NULL,
  showText = TRUE,
  showLegend = TRUE
)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_residuals(
  x,
  analyses = NULL,
  interactive = TRUE,
  xLab = NULL,
  yLab = NULL,
  title = NULL,
  colorGroups = NULL,
  showText = TRUE,
  showLegend = TRUE,
  colorBy = "results"
)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_residual_distance(x, ...)

# S3 method for class 'StatisticResults_PCA_mdatools'
plot_overview(x, ...)

Arguments

model

An object of class pca from the mdatools package.

x

A StatisticResults_PCA_mdatools object.

object

A StatisticResults_PCA_mdatools object.

...

Additional arguments passed to the plot function.

data

A data frame containing the new data to test or predict.

interactive

Logical (length 1). When TRUE, the data is plotted interactively using plotly.

xLab

A string with the title for the x axis.

yLab

A string with the title for the y axis.

title

A string with the title.

showText

Logical (length 1), set to TRUE to show the text annotations.

showLegend

Logical (length 1). Set to TRUE to show legend.

analyses

Character or numeric vector with names or indexes of analyses in the Analyses object.

pcs

A vector of integers specifying which principal components to plot (default is 1:2).

colorGroups

A factor character vector with the color groups for the data.

colorBy

A string defining how to legend the plot. Possible values are analyses, targets (the default) or replicates.

colorKey

A vector of colors to use for the loadings (optional).

Methods (by generic)

  • validate_object(StatisticResults_PCA_mdatools): Validate the object, returning NULL if valid.

  • summary(StatisticResults_PCA_mdatools): Print a summary of the model.

  • get_model_data(StatisticResults_PCA_mdatools): Get the model data as a list of data frames.

  • predict(StatisticResults_PCA_mdatools): Predict new data using the PCA model.

  • test(StatisticResults_PCA_mdatools): Test new data using the PCA model.

  • plot_explained_variance(StatisticResults_PCA_mdatools): Plot the explained variance of the PCA model.

  • plot_scores(StatisticResults_PCA_mdatools): Plot the scores of the PCA model.

  • plot_loadings(StatisticResults_PCA_mdatools): Plot the loadings of the PCA model.

  • plot_residuals(StatisticResults_PCA_mdatools): Plot the residuals of the PCA model.

  • plot_residual_distance(StatisticResults_PCA_mdatools): Plot residual distances of the PCA model.

  • plot_overview(StatisticResults_PCA_mdatools): Plot the explained variance of the PCA model.

Functions

  • plot_cumulative_explained_variance(StatisticResults_Model): Plot the cumulative explained variance of the PCA model.