Weighted linear regression with confidence interval fitted to error bars

GLM.jl’s glm does not interpret the weights wts as inverse variances but as prior frequencies:

    - `wts::Vector=similar(y,0)`: Prior frequency (a.k.a. case) weights of observations.
      Such weights are equivalent to repeating each observation a number of times equal
      to its weight. Do note that this interpretation gives equal point estimates but
      different standard errors from analytical (a.k.a. inverse variance) weights and
      from probability (a.k.a. sampling) weights which are the default in some other
      software.
      Can be length 0 to indicate no weighting (default).