normPlot {berryFunctions} | R Documentation |

## Normal density plot

### Description

Nice plot of normal density distribution

### Usage

```
normPlot(
mean = 0,
sd = 1,
width = 3,
lines = TRUE,
quant = TRUE,
fill = addAlpha("blue", c(2:6, 7:2)/10),
cumulative = TRUE,
las = 1,
main = paste("Normal density with\nmean =", signif(mean, 2), "and sd =", signif(sd,
2)),
ylim = lim0(dnorm(mean, mean, sd)),
ylab = "",
xlab = "",
type = "n",
lty = 1,
col = par("fg"),
mar = c(2, 3, 3, 3),
keeppar = FALSE,
...
)
```

### Arguments

`mean` |
average value as in |

`sd` |
standard deviation. DEFAULT: 1 |

`width` |
distance (in sd) from plot ends to mean. DEFAULT: 3 |

`lines` |
Should vertical lines be plotted at mean +- n*sd? DEFAULT: TRUE |

`quant` |
should quantile regions be drawn with |

`fill` |
color(s) passed to |

`cumulative` |
Should cumulative density distribution be added? DEFAULT: TRUE |

`las` |
arguments passed to |

`main` |
main as in |

`ylim` |
limit for the y axis. DEFAULT: lim0(y) |

`ylab` , `xlab` |
labels for the axes. DEFAULT: "" |

`type` , `lty` , `col` |
arguments passed to |

`mar` |
margins for plot passed to |

`keeppar` |
should margin parameters be kept instead of being restored to previous value? DEFAULT: FALSE |

`...` |
further arguments passed to |

### Details

This function finds some nice defaults for very quickly plotting a normal distribution by just specifying mean and sd.

### Value

None. Used for plotting.

### Author(s)

Berry Boessenkool, berry-b@gmx.de, July 2014

### See Also

`betaPlot`

, `dnorm`

,
https://cran.r-project.org/package=denstrip,
https://cran.r-project.org/view=Distributions

### Examples

```
normPlot()
normPlot(81.7, 11.45)
normPlot(180, 11, quant=FALSE, width=2)
```

*berryFunctions*version 1.22.5 Index]