title: Plotting a survival curve from a survreg prediction
body: <p>I'm relatively new to survival analysis and have been used some standard telco churn data example with a sample below called 'telco':</p>
  
  <pre><code>telco &lt;- read.csv(text = "State,Account_Length,Area_Code,Intl_Plan,Day_Mins,Day_Calls,Day_Charge,Eve_Mins,Eve_Calls,Eve_Charge,Night_Mins,Night_Calls,Night_Charge,Intl_Mins,Intl_Calls,Intl_Charge,CustServ_Calls,Churn
  IN,65,415,no,129.1,137,21.95,228.5,83,19.42,208.8,111,9.4,12.7,6,3.43,4,TRUE
  RI,74,415,no,187.7,127,31.91,163.4,148,13.89,196,94,8.82,9.1,5,2.46,0,FALSE
  IA,168,408,no,128.8,96,21.9,104.9,71,8.92,141.1,128,6.35,11.2,2,3.02,1,FALSE
  MT,95,510,no,156.6,88,26.62,247.6,75,21.05,192.3,115,8.65,12.3,5,3.32,3,FALSE
  IA,62,415,no,120.7,70,20.52,307.2,76,26.11,203,99,9.14,13.1,6,3.54,4,FALSE
  NY,161,415,no,332.9,67,56.59,317.8,97,27.01,160.6,128,7.23,5.4,9,1.46,4,TRUE")
  </code></pre>
  
  <p>I've run:</p>
  
  <pre><code>library(survival)
  
  dependentvars = Surv(telco$Account_Length, telco$Churn)
  
  telcosurvreg = survreg(dependentvars ~ -Churn -Account_Length, dist="gaussian",data=telco)
  
  telcopred = predict(telcosurvreg, newdata=telco, type="quantile", p=.5)
  </code></pre>
  
  <p>...to get the predicted lifetime of each customer.</p>
  
  <p>What I'm struggling with is how to visualise a survival curve for this. Is there a way (preferably in ggplot2) to do this from the data I have?</p>