ldose_function(theta,data=y){
# Data has 3 columns dose, n, success. Gives negative loglikelihood
alpha_theta[1]
beta_theta[2]
prob_exp(alpha+beta*data[,1])/(1+exp(alpha+beta*data[,1]))
like_sum(data[,3]*log(prob)+(data[,2]-data[,3])*log(1-prob))
-like}

maxdose_function(thetint=c(-5,3),data=y){
xx_nlminb(thetint,ldose,data=data)
xx$parameters}

plotdose <- function(alpha=seq(-6,-3,.1),beta=seq(2.5,3.5,.05),data=y){
  #does perspective plot of extreme likelihood surface
  n1 <- length(alpha)
  n2 <- length(beta)
  parest <- maxdose(data=data)
  zmax <- -ldose(parest,data=data)
  z <- matrix(0,n1,n2)
  for(i in 1:n1){for(j in 1:n2){
    z[i,j] <-  -ldose(c(alpha[i],beta[j]),data=data)-zmax}}
persp(alpha,beta,z,xlab="alpha",ylab="beta",zlab="Rel.Like.")
list(alpha=alpha,beta=beta,z=z)}

plotdose1 <- function(gamma=seq(1.3,1.8,.01),beta=seq(2,5,.05),data=y){
  #does perspective plot of extreme likelihood surface
  n1 <- length(gamma)
  n2 <- length(beta)
  
  zmax <- -119.894
  z <- matrix(0,n1,n2)
  for(i in 1:n1){for(j in 1:n2){
    z[i,j] <-  -ldose1(c(gamma[i],beta[j]),data=data)-zmax}}
persp(gamma,beta,z,xlab="gamma",ylab="beta",zlab="Rel.Like.")
list(gamma=gamma,beta=beta,z=z)}

ldose1_function(theta,data=y){
# Data has 3 columns dose, n, success. Gives negative loglikelihood
# Set up for gamma and beta
alpha_-theta[1]*theta[2]
beta_theta[2]
prob_exp(alpha+beta*data[,1])/(1+exp(alpha+beta*data[,1]))
like_sum(data[,3]*log(prob)+(data[,2]-data[,3])*log(1-prob))
-like}