title: R Is there a way to do thresholding in linear regression?
body: <p>I'm trying to do a linear regression but I'm only looking to use variables with positive coefficients (I think this is called hard-thresholding, but I'm not certain).</p>
  
  <p>for example:</p>
  
  <pre><code>&gt; summary(lm1)
  
  Call:
  lm(formula = value ~ ., data = intCollect1[, -c(1, 3)])
  
  Residuals:
       Min       1Q   Median       3Q      Max 
  -15.6518  -0.2089  -0.0227   0.2035  15.2235 
  
  Coefficients:
                  Estimate Std. Error t value Pr(&gt;|t|)    
  (Intercept)     0.099763   0.024360   4.095 4.22e-05 ***
  modelNum3802    0.208867   0.008260  25.285  &lt; 2e-16 ***
  modelNum8000   -0.086258   0.013104  -6.582 4.65e-11 ***
  modelNum8001   -0.058225   0.010741  -5.421 5.95e-08 ***
  modelNum8002   -0.001813   0.012087  -0.150 0.880776    
  modelNum8003   -0.083646   0.011015  -7.594 3.13e-14 ***
  modelNum8004    0.002521   0.010729   0.235 0.814254    
  modelNum8005    0.301286   0.011314  26.630  &lt; 2e-16 ***
  </code></pre>
  
  <p>In the above regression, I would only want to use models 3802, 8004 and 8005.  Is there a way to do this without copying and pasting each variable name?</p>