Description Usage Arguments Details Value Warning Note Author(s) References Examples

Builds data for a 4-parameters Weibull distribution of a given x data

1 2 | ```
weibull4.build(x=seq(0,1,length.out=10), shape=2.5, scale=1, loc=0, area=20,
shape2=5, scale2=2, loc2=6, area2=1, modes=1)
``` |

`x` |
Vector: data range for calculation of the Weibull distribution. If it is NULL, it will be set to seq(0,1,0.1) |

`shape` |
Weibull's shape parameter |

`scale` |
Weibull's scale parameter |

`loc` |
Weibull's location parameter |

`area` |
Weibull's area parameter: area under the PDF curve |

`shape2` |
second mode Weibull's shape parameter. It works only if modes=2. |

`scale2` |
second mode Weibull's scale parameter. It works only if modes=2. |

`loc2` |
second mode Weibull's location parameter. It works only if modes=2. |

`area2` |
second mode Weibull's area parameter. It works only if modes=2. |

`modes` |
Sets whether data may be fit with unimodal or bimodal Weibull distribution. This option was implemented to fit data feom the second wave of infections and deaths for COVID-19. Use modes=1 for unimodal distribution (single peak) and modes=2 for bimodal distribution (two peaks). |

This package was specially built to fit COVID-19 data on the number of daily new cases and deaths in countries. So x must be integer. Alternatively, Date format is allowed

Vector: f(x) Weibull distribution's ordinate

This package is a secondary product of the reffered science paper. Please, note that there is no warrants or professional support on its use

Comments, suggestions and doubts must be sent to vitorhmc@ufba.br

Vitor Hugo Moreau, Ph.D.

MOREAU, V. H. (2021) Using the Weibull distribution to model COVID-19 epidemic data. Modeling Assited Statistics Applications, 2021, in press.

1 2 3 4 5 6 7 8 9 10 | ```
## Build a 4-parameters Weibull distribution with given parameters
weibull4.build(seq(1,100,1), shape=2.5, scale=30, loc=10, area=1000, modes=1)
## Build and plot 4-parameters Weibull distribution with given parameters
plot(seq(1,100,1), weibull4.build(seq(1,100,1), 2, 30, 10, 1), type="l")
## Build and plot 4-parameters Weibull distribution with a time series in the abscissa
Date <- seq(Sys.Date(), as.Date("2022-12-31"),1)
plot(Date, weibull4.build(Date, 1.6, 100, 100, 100), type="l")
## Build and plot a bimodal, 4-parameters Weibull distribution with given parameters
weibull4.build(seq(1,100,1), shape=2.5, scale=30, loc=10, area=1000,
shape2=2.5, scale2=60, loc2=40, area2=1000, modes=2)
``` |

weibull4 documentation built on Jan. 26, 2021, 1:06 a.m.

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