Convert data.frame to time series

I have a question on how to convert a df to a time series. I am new with R and I am struggling with this operation.

These are some rows of my df which is named “test”:

> test
SM    weekY   week       art   cat   flagP Woy   year  ispromo    yval  yqta price ln_yval ln_price
   <chr> <chr>   <date>     <chr> <chr> <chr> <chr> <chr> <chr>     <dbl> <dbl> <dbl>   <dbl>    <dbl>
 1 11111 2016/01 2016-01-03 Z0005 C10   0     01    2016  0        59839.  4060  14.7   11.0      2.69
 2 11111 2016/02 2016-01-10 Z0005 C10   0     02    2016  0        38186.  2640  14.5   10.6      2.67
 3 11111 2016/03 2016-01-17 Z0005 C10   0     03    2016  0        38986.  2660  14.7   10.6      2.68

My date variable is “week”, which doesn’t have necessarily a frequency equal to 7 because some dates are missing. I would like to convert this df to a time series, where “week” is the date to consider. My aim is to use this df for forecasting purposes. In particular, I would like to use multiple linear regression applied to time series

####example where XXXXXXX is the converted df to time series and I am using some variables for lin. regr.

fit_test <- tslm(ln_yval ~ SM + cat + ispromo, data=XXXXXXX)
autoplot(XXXXXXX[,'ln_yval '], series="Data") +
  autolayer(fitted(fit_test), series="Fitted")

Thank you for your help

library(xts)
library(zoo)
library(forecast)

df <- data.frame(week = c("2020-01-01", "2020-01-08", "2020-01-18"),
                 SM = c(1, 2, 3),
                 ispromo = c(0,0,0),
                 cat = c("Z005", "Z005","Z005"),
                 yval = c(1.0, 2.0, 3.0),
                 ln_yval = c(3.4, 4.5, 4.6))
time_series_xts <- xts(df[,-1], order.by=as.Date(df[,1]))
time_series_zoo <- zoo(df[,-1], order.by=as.Date(df[,1]))