rra.test {iRRA} | R Documentation |
This function tests two ROC curves and check which one has the best RRA. It can get as input either two "rra_result" objects or two ROC curves based on the same data set (AN and AP values are the same for both curves)
rra.test(...) ## Default S3 method: rra.test(roc_x_1, roc_y_1, roc_x_2, roc_y_2, AP, AN, ...) ## S3 method for class 'rra_result' rra.test(rra_result_1, rra_result_2, plot = TRUE, col1 = "black", col2 = "red", cUnder1 = "light blue", cUnder2 = "yellow", lty1 = "dashed", ...) ## S3 method for class 'list' rra.test(list1, list2 = c(), AP, AN, plot = TRUE, legend = FALSE, colBest = "black", lwdBest = 2, ltyBest = "solid", cUnderBest = "light blue", lwdOther = 1, ltyOther = "dashed", addcUnderOthers = FALSE, ...)
roc_x_1 |
The |
roc_y_1 |
The |
roc_x_2 |
The |
roc_y_2 |
The |
AP |
The number of actual positives. This value represents the number of positive responses (the "1" values) used to build the ROC curve. It must be greater than |
AN |
The number of actual negatives. This value represents the number of negative responses (the "0" values) used to build the ROC curve. It must be greater or equal to |
rra_result_1 |
The first "rra_result" object to test |
rra_result_2 |
The second "rra_result" object to test |
plot |
If the user wants to plot the two ROC curves and their RoIs |
col1 |
The color of the first ROC curve when plotted |
col2 |
The color of the second ROC curve when plotted |
cUnder1 |
The color of the first RoI space under the curve |
cUnder2 |
The color of the second RoI space under the curve |
lty1 |
The style of the "worst" curve. It corresponds to |
list1 |
Either a list of "rra_result" object or a list of vectors containing the |
list2 |
A list of vectors containing the |
legend |
If the user wants to plot a legend of the drawn ROC curves |
colBest |
Line's color of the ROC curve with the best RRA value |
lwdBest |
Line's width of the ROC curve with the best RRA value |
ltyBest |
Line's style of the ROC curve with the best RRA value |
cUnderBest |
Color of the RoI under the curve with the best RRA value |
lwdOther |
Line's width of the other ROC curves |
ltyOther |
Line's style of the other ROC curves |
addcUnderOthers |
If the user wants to draw the RoI under the other curves |
... |
Other parameters that can be set. Especially:
|
It is possible to plot the two ROC curves and their RoIs.
The method for class "list" will return a vector of the indices of the parameters' list ordered by their RRA values.
It's possible to test any "rra_result" object, but when two curves are generated by different data sets (AN and AP values have different values for the two curves), or when the RoI is computed by different performance metrics, the user will be warned.
rra.plot
parameters col, lwd, lty and cUnder
are overwritten by colBest, lwdBest, ltyBest and cUnderBest
in the method for class "list". It is possible to use both but it will give an error if used at the same time.
The color of the other curves in rra.test.list
is randomly selected by a list of colors.
By default the RoI under the curve of the other curves will not be drawn to make the plot easier to understand. Consider that, if the "rra_result" object considered have different RoI and RoI under the curve (diferent data-set or different reference metrics), one may want to set AddcUnderOthers=TRUE
## Not run: # Considering rra_result_1 <- rra(roc_x, roc_y, AP, AN, phi = TRUE, fallout = 0.5), # and rra_result_2 <- rra(roc2_x, roc2_y, AP, AN, phi = TRUE, fallout = 0.5) # (both ROC curves made from the same data set) # If we consider the rra_result_2 better than the other, rra.test(rra_result_1, rra_result_2, colUnder1 = "green", col1 = "purple") > The second ROC curve (red) has a better RRA value than the first one (purple) rra.test(roc$x, roc$y, roc2$x, roc2$y, AP, AN, phi = TRUE, fallout = TRUE, c_fallout = 0.5) > The second ROC curve (red) has a better RRA value than the first one (black) # Considering rra_result_1 <- rra(roc_x_1, roc_y_1, AP, AN, fallout = TRUE, c_fallout = 0.6, j = TRUE, c_j = 0.35, phi = TRUE), #and rra_result_2 <- rra(roc_x_2, roc_y_2, AP, AN, npv = TRUE, markedness = TRUE, c_markedness = 0.4), # rra.test(rra_result_1, rra_result_2) > The second ROC curve (red) has a better RRA value than the first one (black) > Warning message: > In rra.test.rra_result(rra_result_1, rra_result_2) : > The Regions of Interest considered have been made by > different performance metrics or different metrics' values as references ## End(Not run)