# tsreg Does a time series regression. Different from `lm`. `lm` is a general regression function, so it doesn't do what you want for time series regression. `tsreg` returns the following in its output: - Everything in `lm` output. - `$resids`: The residuals (as a ts object) - `$fitted`: The fitted values (as a ts object) - `$start`: The first observation used in the regression data. - `$end`: The last observation used in the regression data. - `$int`: `TRUE` or `FALSE` to denote whether there's an intercept in the regression. # Arguments `tsreg <- function(y.raw, x.raw, start=NULL, end=NULL, intercept=TRUE)` - `y.raw`: A ts object. The left side of the regression. - `x.raw`: A ts object (may be mts). The right side of the regression. - `start`: Optional starting date for the regression. - `end`: Optional ending date for the regression. - `intercept`: `TRUE` if there's an intercept in the regression, `FALSE` otherwise. # Examples ``` tsreg(y, x) tsreg(y, x, start=c(2014,1)) tsreg(y, x, end=c(2019,12)) tsreg(y, x, start=c(2000,6), end=c(2018,4)) fit <- tsreg(y, x, intercept=FALSE) # Can treat the output like lm - because it is AIC(fit) coefficients(fit) summary(fit) # ts properties fit$resids fit$fitted fit$start fit$end ```
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