plotRMSE {benchdamic} | R Documentation

## plotRMSE

### Description

A function to plot RMSE values computed for mean difference (MD) and zero probability difference (ZPD) values between estimated and observed values.

### Usage

    plotRMSE(data, difference = NULL, plotIt = TRUE)

### Arguments

`data` | a list, output of the `fitModels` function or a 'data.frame' object with `Model`, `Y`, `Y0`, `MD`, and `ZPD` columns containing the model name, the observed values for the mean and the zero proportion and the differences between observed and estimated values.
`difference` | character vector, either `MD` or `ZPD` to plot the differences between estimated and observed mean counts or the differences between estimated zero probability and observed zero proportion.
`plotIt` | logical. Should plotting be done? (default `plotIt = TRUE`)

### Value

a `ggplot` object.

### See Also

`fitModels` and `RMSE` for the model estimations and the RMSE computations respectively. `plotMD` for the graphical evaluation.

### Examples

    # Generate some random counts
    counts = matrix(rnbinom(n = 60, size = 3, prob = 0.5), nrow = 10, ncol = 6)

    # Estimate the counts assuming several distributions
    GOF <- fitModels(
        counts = counts, models = c(
            "NB", "ZINB",
            "DM", "ZIG", "HURDLE"
        ), scale_ZIG = c("median", "default"), scale_HURDLE =
            c("median", "default")
    )

    # Plot the RMSE results
    plotRMSE(data = GOF, difference = "MD")
    plotRMSE(data = GOF, difference = "ZPD")

[Package benchdamic version 1.0.0 Index]