VB {AgroReg} | R Documentation |

## Analysis: Von Bertalanffy

### Description

The Von Bertalanffy model. It's a kind of growth curve for a time series and takes its name from its creator, Ludwig von Bertalanffy. It is a special case of the generalized logistic function. The growth curve (biology) is used to model the average length from age in animals.

### Usage

```
VB(
trat,
resp,
initial = NA,
sample.curve = 1000,
ylab = "Dependent",
xlab = "Independent",
theme = theme_classic(),
legend.position = "top",
r2 = "all",
error = "SE",
point = "all",
width.bar = NA,
scale = "none",
textsize = 12,
pointsize = 4.5,
linesize = 0.8,
linetype = 1,
pointshape = 21,
fillshape = "gray",
colorline = "black",
round = NA,
yname.formula = "y",
xname.formula = "x",
comment = NA,
fontfamily = "sans"
)
```

### Arguments

`trat` |
Numeric vector with dependent variable. |

`resp` |
Numeric vector with independent variable. |

`initial` |
Starting estimates |

`sample.curve` |
Provide the number of observations to simulate curvature (default is 1000) |

`ylab` |
Variable response name (Accepts the |

`xlab` |
Treatments name (Accepts the |

`theme` |
ggplot2 theme ( |

`legend.position` |
Legend position ( |

`r2` |
Coefficient of determination of the mean or all values ( |

`error` |
Error bar (It can be SE - |

`point` |
Defines whether you want to plot all points ("all") or only the mean ("mean") |

`width.bar` |
Bar width |

`scale` |
Sets x scale ( |

`textsize` |
Font size |

`pointsize` |
Shape size |

`linesize` |
Line size |

`linetype` |
line type |

`pointshape` |
Format point (default is 21) |

`fillshape` |
Fill shape |

`colorline` |
Color lines |

`round` |
round equation |

`yname.formula` |
Name of y in the equation |

`xname.formula` |
Name of x in the equation |

`comment` |
Add text after equation |

`fontfamily` |
Font family |

### Details

The model function for the von Bertalanffy model is:

` y = L(1-exp(-k(t-t0)))`

### Value

The function returns a list containing the coefficients and their respective values of p; statistical parameters such as AIC, BIC, pseudo-R2, RMSE (root mean square error); largest and smallest estimated value and the graph using ggplot2 with the equation automatically.

### Author(s)

Gabriel Danilo Shimizu

Leandro Simoes Azeredo Goncalves

### Examples

```
library(AgroReg)
x=seq(1,20)
y=c(0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 0.91,
0.92, 0.94, 0.96, 0.98, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00)
VB(x,y)
```

*AgroReg*version 1.2.10 Index]