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I have the following code for minimizing the sum of deviation using optim() to find beta0 and beta1 but I am receiving the following errors I am not sure what I am doing wrong:

sum.abs.dev<-function(beta=c(beta0,beta1),a,b)
{
  total<-0
  n<-length(b)
  for (i in 1:n)
  {
    total <- total + (b[i]-beta[1]-beta[2]*a[i])
  }
  return(total)
}
tlad <- function(y = "farm", x = "land", data="FarmLandArea.csv")
{

  dat <- read.csv(data)

  #fit<-lm(dat$farm~dat$land)
  fit<-lm(y~x,data=dat)
  beta.out=optim(fit$coefficients,sum.abs.dev)

  return(beta.out)
}

Here's the error and warnings are receive:

Error in `contrasts<-`(`*tmp*`, value = contr.funs[1 + isOF[nn]]) : 
  contrasts can be applied only to factors with 2 or more levels In addition: Warning message:
In model.response(mf, "numeric") : NAs introduced by coercion

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Mona Jalal
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1 Answers1

5

There are several problems here:

  1. You are specifying variables as character strings, so this line (fit<-lm(y~x,data=dat)) is interpreted by R as fit<-lm("farm"~"land",data=dat).
  2. It is easier to not specify default variables in your function because of scoping issues.

I would consider the following instead:

tlad <- function(y, x){      
  fit <- lm(y~x)
  beta.out <- optim(fit$coefficients, sum.abs.dev)
  return(beta.out)
}

dat <- read.csv("FarmLandArea.csv")
tlad(dat$farm, dat$land)
Thomas
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