PlotLocalSens {capm} R Documentation

## Plot results of CalculateLocalSens function

### Description

Plot results of the `CalculateLocalSens` function.

### Usage

```PlotLocalSens(local.out = NULL, x.sens = "Time",
y.sens = "Sensitivity", y.ind = c("L1", "L2", "Mean", "Min", "Max"),
bar.colors = "DarkRed", label.size = 10, x.axis.angle = 90,
type = 1)
```

### Arguments

 `local.out` output from `CalculateLocalSens` function. `x.sens` string with the name for the x axis. `y.sens` string with the name for the y axis of the sensitivity functions (when `type = 6`). `y.ind` string with the name for the y axis of the parameter importance indices. `bar.colors` any valid specification of a color. `label.size` a number to specify the size of axes labels and text. `x.axis.angle` a number with angle of rotation for x axis text. Passed to `angle` argument of `element_text`. `type` a number to define the type of graphical output. `1`: importance index L1; `2`: importance index L2; `3`: mean of sensitivity functions; `5`: minimum of sensitivity functions; and `5`: maximum of sensitivity functions; `6`: sensitivity functions and all importance indices are ploted.

### Details

Font size of saved plots is usually different to the font size seen in graphic browsers. Before changing font sizes, see the final result in saved (or preview) plots.

### References

Chang W (2012). R Graphics Cookbook. O'Reilly Media, Inc.

Soetaert K, Cash J and Mazzia F (2012). Solving differential equations in R. Springer.

Baquero, O. S., Marconcin, S., Rocha, A., & Garcia, R. D. C. M. (2018). Companion animal demography and population management in Pinhais, Brazil. Preventive Veterinary Medicine.

### Examples

```## IASA model#'
## Parameters and intial conditions.
data(dogs)
dogs_iasa <- GetDataIASA(dogs,
destination.label = "Pinhais",
total.estimate = 50444)
# Solve for point estimates.
solve_iasa_pt <- SolveIASA(pars = dogs_iasa\$pars,
init = dogs_iasa\$init,
time = 0:15,
alpha.owned = TRUE,
method = 'rk4')
## Calculate local sensitivities to all parameters.
local_solve_iasa2 <- CalculateLocalSens(
model.out = solve_iasa_pt, sensv = "n2")
## Plot local sensitivities
PlotLocalSens(local_solve_iasa2)

```

[Package capm version 0.14.0 Index]