Hi, and welcome!
It's a good practice to include a reproducible example, called a reprex to attract more and quicker answers.
I used a help example which renders in the console
library(urca)
data(nporg)
gnp <- na.omit(nporg[, "gnp.r"])
df.gnp <- ur.df(gnp, type="trend", lags=4)
summary(df.gnp)
#>
#> ###############################################
#> # Augmented Dickey-Fuller Test Unit Root Test #
#> ###############################################
#>
#> Test regression trend
#>
#>
#> Call:
#> lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
#>
#> Residuals:
#> Min 1Q Median 3Q Max
#> -42.492 -9.887 0.912 9.861 25.634
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) -2.71394 4.63380 -0.586 0.561
#> z.lag.1 -0.02785 0.04211 -0.661 0.511
#> tt 0.61613 0.38509 1.600 0.116
#> z.diff.lag1 0.33761 0.14502 2.328 0.024 *
#> z.diff.lag2 0.02606 0.15108 0.173 0.864
#> z.diff.lag3 -0.05841 0.15099 -0.387 0.701
#> z.diff.lag4 -0.19280 0.15010 -1.284 0.205
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Residual standard error: 15.31 on 50 degrees of freedom
#> Multiple R-squared: 0.3033, Adjusted R-squared: 0.2197
#> F-statistic: 3.628 on 6 and 50 DF, p-value: 0.004582
#>
#>
#> Value of test-statistic is: -0.6614 4.2327 3.2833
#>
#> Critical values for test statistics:
#> 1pct 5pct 10pct
#> tau3 -4.04 -3.45 -3.15
#> phi2 6.50 4.88 4.16
#> phi3 8.73 6.49 5.47
Created on 2019-12-18 by the reprex package (v0.3.0)
and in a knitted Rmd file
---
title: "urca"
author: "Richard Careaga"
date: "12/18/2019"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(urca)
data(nporg)
gnp <- na.omit(nporg[, "gnp.r"])
df.gnp <- ur.df(gnp, type="trend", lags=4)
summary(df.gnp)
equally well.