View difference between Paste ID: yTRahzr5 and x9zMQRxv

 %% what I want to do:
 x_true % "true", error-free measurement of a variable over time
 x_noise % synthetic noise, not necessarily homoskedastic and/or normally distributed
 x = x_true + x_noise
 for i = 1:n_boot
     p_est(i) = parameter for best fit of model to x
     x = x_true + resample( x_noise ) % bootstrap x_noise (I guess wild bootstrap would be best here?)
-    end
+end
 
 %% what I believe "normal" bootstrapping of residuals would look like ???
 for i = 1:n_boot
     p_est(i) = parameter for best fit of model to x
     x = x_first_best_fit + resample( x_first_best_fit - x )
 end