#' Finds the correlation matrix of a two variables
#' @param cov Covariance Matrix
#' @param theta rotation in radians
#'
#' @return Line 5 is the s12tilde, the graphs show the relationship between theta and s12tilde
#' @export
#'
#'
mysik2 <- function(cov,theta) {
Sn=cov
s11=Sn[1,1]
s22=Sn[2,2]
s12=Sn[1,2]
myfun=function(x) (s22-s11)*sin(x)*cos(x) +s12*(cos(x)^2-sin(x)^2)
myfun2=function(x) (s22-s11)*1/2*sin(2*x) + s12*(cos(2*x))
my.newt=function(x0,f=myfun,delta=1e-12,epsilon=1e-12,th1=c(0,2*pi),th2=c(0,pi/2),parameter=expression(theta)){
#graphics.off()
# x0 initial value
#f the function to be zeroed
#delta is the increment in the derivative
#epsilon is how close our approximation is to zero
#th1 is the range of rotation angle for NR
#th2 is the range for rotation angle for myfun
fdash=function(x) (f(x+delta)-f(x))/delta
d=1000 # initial values
i=0
x=c() # empty vectors
y=c()
x[1]=x0 # assign initial guess
y[1]=f(x[1]) # initial y value
while(d > epsilon & i<100){ # ensures that it doesnt loop too much
i=i+1
x[i+1]=x[i]-f(x[i])/fdash(x[i]) # NR step
y[i+1]=f(x[i+1]) # update y value
d=abs(y[i+1]) # update d
}
#windows()
#Cut the graphical area into two
layout(matrix(1:2,nr=2,nc=1,byrow=TRUE),heights=c(3,4))
curve(f(x), xlim=th1,xlab=parameter,ylab="f",main="myfun")
abline(h=0,col="Red",lwd=2)
# plot f with no x axis on a reduced x range
curve(f(x),xlim=th2,xaxt="n", xlab=parameter,ylab="f",main= "Newton-Raphson Algorithm")
points(x,y,col="Red",pch=19,cex=0.5)
# Now plot the x axis
axis(1,x,round(x,2),las=2)
abline(h=0,col="Red")
segments(x[1:(i-1)],y[1:(i-1)],x[2:i],rep(0,i-1),col="Blue",lwd=0.5)
segments(x[2:i],rep(0,i-1),x[2:i],y[2:i],lwd=0.5,col="Green")
# paste the root onto the last graph
arrows(x0=x[i+1],y0=y[1],x1=x[i+1],y1=y[i+1])
text(x[i+1],y[1],x[i+1])
nn=length(x)
list(x=x,y=y,d=d, root=x[nn])
}
x=my.newt(1.1,f = myfun, th2=c(0,6))
z=s12tilde=sn[1,1]*cos(theta)*sin(theta)-sn[1,2]*cos(theta)^2+sn[1,2]*sin(theta)^2-sn[2,2]*cos(theta)*sin(theta)
returnline=c(x, z)
return(returnline)
}
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