Hello kind and wise internet friends,
I have been toying with R from various angles, but I seem to have made little progress. This is probably basic, but my mind and experience are more so...
I ultimately want to plot the influence of varying m and n on the output (b) in the equation:
b=(0.15m+0.15n)/n. Where m and n have ranges of -1 to 1.
I envisage a contour plot to visualise this, but I am stuck at the step of getting values of b with corresponding m and n inputs.
The latest approach involved bootstrapping estimates for m and n to return b values, but as far as I am aware there is no way to obtain the corresponding input m and n values:
m<-seq(from=-1,1,length.out=100)
n<-seq(from=-1,1,length.out=100)
z<-rnorm(100)
b<-((0.15*(sample(m,1,replace=T))+0.15*(sample(n,1,replace=T)))/(sample(n,1,replace=T)))
library("boot")
bfunc<-function(m,n){
(0.15*(sample(m,1,replace=T))+0.15*(sample(n,1,replace=T)))/(sample(n,1,replace=T))
}
bootb<-boot(data=z,statistic=(bfunc),R=1000)
bootb$t
My question: How do I get my output (b) and corresponding inputs (m and n), so that I can plot the data? Modifications of the above or entirely different ways are all welcome... I need to learn!
Any help is much appreciated, thank you.
I don't see why you would need the bootstrap
dataset <- expand.grid(
m = seq(-1, 1, length.out = 101),
n = seq(-1, 1, length.out = 101)
)
dataset$b <- (0.15 * dataset$m + 0.15 * dataset$n) / dataset$n
library(ggplot2)
ggplot(dataset, aes(x = m, y = n, z = b)) +
geom_contour(aes(colour = ..level..)) +
scale_colour_gradient2()
ggplot(dataset, aes(x = m, y = n, fill = b)) +
geom_tile() +
scale_fill_gradient2()