R: Plot Factor Merger

plot.factorMerger {factorMerger} | R Documentation

## Plot Factor Merger

### Description

Plot Factor Merger

### Usage

    ## S3 method for class 'factorMerger'
    plot(x, panel = "all", statistic = "loglikelihood",
      nodesSpacing = "equidistant", colorClusters = TRUE,
      splitStatistic = "GIC", splitThreshold = NULL, penalty = 2,
      showSplit = FALSE, showSignificance = TRUE,
      title = "Factor Merger Tree", subtitle = " ", palette = NULL,
      responsePanel = NULL, responsePanelPalette = NULL, gicPanelColor = NULL,
      panelGrid = TRUE, chisqQuantile = 0.05, ...)

### Arguments

`x` | object of a class `factorMerger`.
`panel` | Type of panels to be plot. Possible values are `c("all", "response", "GIC", "tree")`. All types of plots include the Factor Merger Tree. Apart from the Factor Merger Tree there are also two possible panels: the Response Plot (response summary, specific to the model family), the GIC Plot (GIC vs. loglikelihood/p-value). `"all"` plots all panels and a short summary of the full model, `"response"` plots the Factor Merger Tree and the Response Plot, `"GIC"` plots the Factor Merger Tree and the GIC Plot, `"tree"` plots the Factor Merger Tree only.
`statistic` | Statistic to be displayed on the OX axis of the Factor Merger Tree. Possible values are `c("loglikelihood", "p-value")`. If `"p-value"` is chosen p-value for the Likelihood Ratio Test against the full model is plot on the OX axis.
`nodesSpacing` | Type of vertical nodes spacing in the Factor Merger Tree). May be chosen from `c("equidistant", "effects", "modelSpecific")`. `"effects"` arranges nodes according to the model coefficients estimatiors (e.g. in Gaussian case on the OY axis group means are plotted). # TODO: Implement "modelSpecific".
`colorClusters` | Boolean. If `TRUE`, the default, the Factor Merger Tree is colored according to the optimal factor split (defined by `splitStatistic` and `splitThreshold` or `splitStatistic` and `penalty`).
`splitStatistic` | Statistic used in the optimal split definition. Possible values are: `c("GIC", "loglikelihood", "p-value")`. If `"GIC"` is chosen, factor is split to minimize GIC with the penalty `penalty`. Otherwise, chooses the very last partition whose corresponding statistic (model loglikelihood or p-value for the LRT test) is not lower than `splitThreshold`.
`splitThreshold` | Threshold used in the optimal split definition. Used only with `splitStatistic = c("loglikelihood", "p-value")`.
`penalty` | GIC penalty used for defining the optimal partition with `splitStatistic = "GIC"`. The same penalty is used in the GIC plot.
`showSplit` | Boolean. If `TRUE` plots vertical line crossing the optimal split.
`showSignificance` | Boolean. If `TRUE`, the default, marks partitions that are significantly worse than their predecessors on the Factor Merger Tree (uses the Likelihood Ratio Test). Significance codes are: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1.
`title` | Factor Merger Tree plot's title.
`subtitle` | Factor Merger Tree plot's subtitle.
`palette` | Color palette used in the Factor Merger Tree and the Response Plot.
`responsePanel` | Response panel type – accepts the following values dependent on the model family: multi dimensional Gaussian: `c("heatmap", "profile")`, single dimensional Gaussian: `c("means", "boxplot","tukey")`, binomial: `c("proportion")`, survival: `c("survival")`
`responsePanelPalette` | Additional color palette used in the Response Plot if palettes for the Factor Merger Tree and the Response Plot are to be different.
`gicPanelColor` | Color used in the GIC plot.
`panelGrid` | Boolean. If `TRUE`, each interval on the OX axis of the Factor Merger Tree corresponds to the 1 - `chisqQuantile` quantile of chi-square distribution. Otherwise, panel is blank.
`chisqQuantile` | Significance level used if `panelGrid = TRUE`.
`...` | Other arguments

[Package factorMerger version 0.3.6 Index]