Description Usage Arguments Details Value Author(s) References Examples
Calculate the response of species to the range of values in each predictor variable based on the fitted models in a sdmModels object.
1 2 3 | rcurve(x,n,id,mean,confidence,gg,...)
getResponseCurve(x,id,...)
|
x |
A |
id |
specifies the modelIDs corresponding to the models in the sdmModels object for which the response curves should be generated |
n |
A vector with the name of variables for which the response curve should be generated |
mean |
logical, specifies whether a mean should be calculated over responses to a variable when multiple models are specified in ids |
confidence |
logical, specifies whether a confidence interval should be added to the curve when the mean response curve is calculated based on multiple models |
gg |
logical, specifies whether the plot should be generated using the ggplot2 package (if the package is installed) |
... |
additional arguments passed to plot function |
getResponseCurve
calculates the responses for the models that are specified in id
argument, and put the results in a .responseCurve
object. This object can be used as an input in the plot
function, or rcurve
function.
If you just need the response curve graphs (plots), you can put a sdmModels
object directly in the rcurve
function, and do not need to first use getResponseCurve
function.
In getResponseCurve
function (or in rcurve
when x
is sdmModels
), there are some additional arguments:
- size
: a numeric value; default is 100. Specifies the size of the variable sequence that is used as the x-axis in the response curve plot. Greater number results to a smoother curve.
- includeTest
: a logical value; default is FALSE; when a data object based on which a sdmModels is created containing independent test data; it specifies whether those records should be included into the response curve generation or not.
- ...
: additional arguments for the plot
function (e.g., xlab, ylab, main, col, lwd, lty)
an object of class .responseCurve
or a series of graphs
Babak Naimi naimi.b@gmail.com
https://www.biogeoinformatics.org
Naimi, B., Araujo, M.B. (2016) sdm: a reproducible and extensible R platform for species distribution modelling, Ecography, 39:368-375, DOI: 10.1111/ecog.01881
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | ## Not run:
file <- system.file("external/model.sdm", package="sdm")
m <- read.sdm(file) # a sdmModels Object (fitted using sdm function)
rcurve(m)
rcurve(m,id=1) # for the first model
rcurve(m, id=1:2)
rcurve(m,method = 'glm',smooth = T) # only for models fitted using glm method & with smoothed curve
## End(Not run)
|
Loading required package: sp
sdm 1.0-67 (2019-02-26)
The id is missing; the first successfully fitted model is considered, i.e., id = 1
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Attaching package: 'nlme'
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getData
This is mgcv 1.8-28. For overview type 'help("mgcv-package")'.
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randomForest 4.6-14
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Attaching package: 'kernlab'
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Attaching package: 'ggplot2'
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margin
The id is missing; the first successfully fitted model is considered, i.e., id = 1
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