Ord_plot | R Documentation |

Ord plots for diagnosing discrete distributions.

Ord_plot(obj, legend = TRUE, estimate = TRUE, tol = 0.1, type = NULL, xlim = NULL, ylim = NULL, xlab = "Number of occurrences", ylab = "Frequency ratio", main = "Ord plot", gp = gpar(cex = 0.5), lwd = c(2,2), lty=c(2,1), col=c("black", "red"), name = "Ord_plot", newpage = TRUE, pop = TRUE, return_grob = FALSE, ...) Ord_estimate(x, type = NULL, tol = 0.1)

`obj` |
either a vector of counts, a 1-way table of frequencies of counts or a data frame or matrix with frequencies in the first column and the corresponding counts in the second column. |

`legend` |
logical. Should a legend be plotted?. |

`estimate` |
logical. Should the distribution and its parameters be estimated from the data? See details. |

`tol` |
tolerance for estimating the distribution. See details. |

`type` |
a character string indicating the distribution, must be
one of |

`xlim` |
limits for the x axis. |

`ylim` |
limits for the y axis. |

`xlab` |
a label for the x axis. |

`ylab` |
a label for the y axis. |

`main` |
a title for the plot. |

`gp` |
a |

`lwd, lty` |
vectors of length 2, giving the line width and line type used for drawing the OLS line and the WLS lines. |

`col` |
vector of length 2 giving the colors used for drawing the OLS and WLS lines. |

`name` |
name of the plotting viewport. |

`newpage` |
logical. Should |

`pop` |
logical. Should the viewport created be popped? |

`return_grob` |
logical. Should a snapshot of the display be returned as a grid grob? |

`...` |
further arguments passed to |

`x` |
a vector giving intercept and slope for the (fitted) line in the Ord plot. |

The Ord plot plots the number of occurrences against a certain frequency ratio (see Friendly (2000) for details) and should give a straight line if the data comes from a poisson, binomial, negative binomial or log-series distribution. The intercept and slope of this straight line conveys information about the underlying distribution.

`Ord_plot`

fits a usual OLS line (black) and a weighted OLS line
(red). From the coefficients of the latter the distribution is
estimated by `Ord_estimate`

as described in Table 2.10 in
Friendly (2000). To judge whether a coefficient is positive or
negative a tolerance given by `tol`

is used. If none of the
distributions fits well, no parameters are estimated. Be careful with
the conclusions from `Ord_estimate`

as it implements just some
simple heuristics!

A vector giving the intercept and slope of the weighted OLS line.

Achim Zeileis Achim.Zeileis@R-project.org

J. K. Ord (1967),
Graphical methods for a class of discrete distributions,
*Journal of the Royal Statistical Society*, **A 130**,
232–238.

Michael Friendly (2000),
*Visualizing Categorical Data*.
SAS Institute, Cary, NC.

## Simulated data examples: dummy <- rnbinom(1000, size = 1.5, prob = 0.8) Ord_plot(dummy) ## Real data examples: data("HorseKicks") data("Federalist") data("Butterfly") data("WomenQueue") ## Not run: grid.newpage() pushViewport(viewport(layout = grid.layout(2, 2))) pushViewport(viewport(layout.pos.col=1, layout.pos.row=1)) Ord_plot(HorseKicks, main = "Death by horse kicks", newpage = FALSE) popViewport() pushViewport(viewport(layout.pos.col=1, layout.pos.row=2)) Ord_plot(Federalist, main = "Instances of 'may' in Federalist papers", newpage = FALSE) popViewport() pushViewport(viewport(layout.pos.col=2, layout.pos.row=1)) Ord_plot(Butterfly, main = "Butterfly species collected in Malaya", newpage = FALSE) popViewport() pushViewport(viewport(layout.pos.col=2, layout.pos.row=2)) Ord_plot(WomenQueue, main = "Women in queues of length 10", newpage = FALSE) popViewport(2) ## End(Not run) ## same mplot( Ord_plot(HorseKicks, return_grob = TRUE, main = "Death by horse kicks"), Ord_plot(Federalist, return_grob = TRUE, main = "Instances of 'may' in Federalist papers"), Ord_plot(Butterfly, return_grob = TRUE, main = "Butterfly species collected in Malaya"), Ord_plot(WomenQueue, return_grob = TRUE, main = "Women in queues of length 10") )

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