Summary of linear regression (for a time series)

tidy_reg(x, reg_dat, n_preds = 10, ...)

# S3 method for lm
tidy_reg(x, reg_dat, n_preds = 10, ..., conf.level = 0.95)

# S3 method for openair
tidy_reg(x, reg_dat, n_preds = 10, ..., adjust_x0 = TRUE)

Arguments

x: A regression object created via stats::lm() or openair::TheilSen()
reg_dat: The exact same dataset that was also provided when creating x above
n_preds: Number of evenly spread out points on the x-axis for which predictions (including confidence interval) should be made
...: Other arguments passed to broom::tidy() from lm models.
conf.level: The confidence level to use for the confidence interval
adjust_x0: If TRUE (default) the estimate and confidence limits for the intercept are adjusted so that it is no longer at openair's default x = 1970, but instead at the minimum x present in the data.